feat(docs): add orq ai community provider documentation and reference

content/docs/02-foundations/02-providers-and-models.mdx

@@ -81,6 +81,7 @@ The open-source community has created the following providers:
 - [A2A Provider](/providers/community-providers/a2a) (`a2a-ai-provider`)
 - [SAP-AI Provider](/providers/community-providers/sap-ai) (`@mymediset/sap-ai-provider`)
 - [AI/ML API Provider](/providers/community-providers/aimlapi) (`@ai-ml.api/aimlapi-vercel-ai`)
+- [Orq AI Provider](/providers/community-providers/orq-ai) (`@orq-ai/vercel-provider`)
 
 ## Self-Hosted Models
 

content/providers/03-community-providers/101-orq-ai.mdx

@@ -0,0 +1,183 @@
+---
+title: Orq AI
+description: Orq AI Provider for the AI SDK
+---
+
+# Orq AI
+
+[Orq AI](https://orq.ai) is a unified platform for AI model deployment and routing that provides seamless access to multiple AI models through a single API endpoint. The Orq AI provider for the AI SDK enables developers to leverage Orq's automatic routing, optimization, and monitoring capabilities while maintaining full compatibility with the AI SDK ecosystem.
+
+## Key Advantages
+
+Orq AI offers several advantages for AI application development:
+
+- **Unified API Access**: Access models from OpenAI, Anthropic, Google, Meta, and more through a single endpoint
+- **Automatic Model Routing**: Intelligently route requests to the best available model based on performance and availability
+- **Performance Monitoring**: Track latency, cost, and quality metrics across all your AI operations
+- **A/B Testing**: Test different models and configurations to optimize performance
+- **Fallback Handling**: Automatic failover to backup models ensures high availability
+- **Cost Optimization**: Balance performance vs. cost trade-offs with intelligent routing
+
+Learn more about Orq AI's capabilities at [orq.ai](https://orq.ai).
+
+## Setup
+
+The Orq AI provider is available via the `@orq-ai/vercel-provider` module. You can install it with:
+
+```bash
+npm install @orq-ai/vercel-provider
+pnpm add @orq-ai/vercel-provider
+yarn add @orq-ai/vercel-provider
+bun add @orq-ai/vercel-provider
+```
+
+## Provider Instance
+
+You can create an instance of the Orq AI provider using the `createOrqAiProvider` function:
+
+```ts
+import { createOrqAiProvider } from '@orq-ai/vercel-provider';
+
+const orq = createOrqAiProvider({
+  apiKey: 'YOUR_ORQ_API', // Replace with your Orq AI API key
+});
+```
+
+You can obtain your Orq AI API key from the [Orq AI dashboard](https://my.orq.ai/).
+
+## Language Models
+
+The Orq AI provider supports a wide range of language models from various providers, all accessible through a unified interface.
+
+```ts
+// Access any supported model (using the orq instance created earlier)
+const model = orq('openai/gpt-4o');
+```
+
+You can also use specific model types:
+
+```ts
+// Chat models (default)
+const chatModel = orq.chatModel('openai/gpt-4o');
+
+// Completion models
+const completionModel = orq.completionModel('openai/gpt-3.5-turbo-instruct');
+```
+
+## Examples
+
+### generateText
+
+Generate text with various models:
+
+```ts
+import { generateText } from 'ai';
+
+const { text } = await generateText({
+  model: orq('openai/gpt-4o'),
+  system: 'You are a helpful assistant.',
+  prompt: 'What is the capital of France?',
+});
+
+console.log(text);
+```
+
+### streamText
+
+Stream responses for real-time interaction:
+
+```ts
+import { streamText } from 'ai';
+
+const result = streamText({
+  model: orq('openai/gpt-4o'),
+  prompt: 'Invent a new holiday and describe its traditions.',
+});
+
+// Use textStream as an async iterable
+for await (const textPart of result.textStream) {
+  console.log(textPart);
+}
+```
+
+## Embedding Models
+
+Orq AI provides access to various embedding models for semantic search and similarity computations:
+
+```ts
+import { embed, embedMany } from 'ai';
+
+// Single embedding
+const { embedding } = await embed({
+  model: orq.textEmbeddingModel('openai/text-embedding-ada-002'),
+  value: 'The quick brown fox jumps over the lazy dog',
+});
+
+// Multiple embeddings
+const { embeddings } = await embedMany({
+  model: orq.textEmbeddingModel('openai/text-embedding-ada-002'),
+  values: [
+    'First document about AI',
+    'Second document about machine learning',
+    'Third document about deep learning',
+  ],
+});
+```
+
+## Image Generation
+
+Create images using AI models:
+
+```ts
+import { experimental_generateImage as generateImage } from 'ai';
+
+const { image } = await generateImage({
+  model: orq.imageModel('openai/dall-e-3'),
+  prompt: 'A futuristic city with flying cars at sunset',
+  size: '1024x1024',
+  n: 1,
+  aspectRatio: '1:1',
+  seed: undefined,
+  providerOptions: {
+    openai: {
+      style: 'vivid',
+      quality: 'hd',
+    },
+  },
+});
+```
+
+## Advanced Configuration
+
+### Custom Headers and Authentication
+
+Add custom headers for organization-specific configurations:
+
+```ts
+const orq = createOrqAiProvider({
+  apiKey: 'YOUR_ORQ_API', // Replace with your Orq AI API key
+  headers: {
+    'X-Organization-Id': 'org-123',
+    'X-Project-Id': 'project-456',
+  },
+});
+```
+
+## Provider Options
+
+The Orq AI provider accepts the following configuration options:
+
+```ts
+interface OrqAiProviderOptions {
+  apiKey: string; // Required: Your Orq API key
+  headers?: Record<string, string>; // Optional: Additional HTTP headers
+}
+```
+
+## Additional Resources
+
+- [Orq AI Platform](https://orq.ai) - Main platform website
+- [Orq AI Documentation](https://docs.orq.ai) - Comprehensive platform documentation
+- [API Reference](https://docs.orq.ai/docs/introduction) - Detailed API documentation
+- [Model Catalog](https://docs.orq.ai/docs/proxy) - Browse available models
+- [Pricing](https://orq.ai/pricing) - Platform pricing information