Run biome format and fix import sorting

Author: subtleGradient

typescript/effect-ai/src/basic/example.ts

@@ -8,13 +8,13 @@
  * - Streaming responses with Effect streams
  */
 
-import * as Chat from "@effect/ai/Chat"
-import * as LanguageModel from "@effect/ai/LanguageModel"
-import * as OpenRouterClient from "@effect/ai-openrouter/OpenRouterClient"
-import * as OpenRouterLanguageModel from "@effect/ai-openrouter/OpenRouterLanguageModel"
-import { FetchHttpClient } from "@effect/platform"
-import * as BunContext from "@effect/platform-bun/BunContext"
-import { Console, Effect, Layer, Redacted, Stream } from "effect"
+import * as OpenRouterClient from '@effect/ai-openrouter/OpenRouterClient';
+import * as OpenRouterLanguageModel from '@effect/ai-openrouter/OpenRouterLanguageModel';
+import * as Chat from '@effect/ai/Chat';
+import * as LanguageModel from '@effect/ai/LanguageModel';
+import { FetchHttpClient } from '@effect/platform';
+import * as BunContext from '@effect/platform-bun/BunContext';
+import { Console, Effect, Layer, Redacted, Stream } from 'effect';
 
 /**
  * Main program using Effect.gen for composable effects
@@ -25,63 +25,63 @@ import { Console, Effect, Layer, Redacted, Stream } from "effect"
  */
 const program = Effect.gen(function* () {
   // Log separator for readability
-  yield* Console.log("\n=== Example 1: Simple Chat Completion ===\n")
+  yield* Console.log('\n=== Example 1: Simple Chat Completion ===\n');
 
   // Generate text using the language model
   // The LanguageModel service is injected via the Effect context
   const response = yield* LanguageModel.generateText({
-    prompt: "Explain what Effect is in functional programming in 2 sentences.",
-  })
+    prompt: 'Explain what Effect is in functional programming in 2 sentences.',
+  });
 
   // Access the generated text from the response
-  yield* Console.log("Response:", response.text)
-  yield* Console.log("Finish reason:", response.finishReason)
-  yield* Console.log("Usage:", response.usage)
+  yield* Console.log('Response:', response.text);
+  yield* Console.log('Finish reason:', response.finishReason);
+  yield* Console.log('Usage:', response.usage);
 
   // Example 2: Stateful conversation with Chat
-  yield* Console.log("\n=== Example 2: Stateful Chat Conversation ===\n")
+  yield* Console.log('\n=== Example 2: Stateful Chat Conversation ===\n');
 
   // Chat.empty creates a new chat session with empty history
   // Chat maintains conversation context across multiple turns
-  const chat = yield* Chat.empty
+  const chat = yield* Chat.empty;
 
   // First turn - the model responds to our greeting
   const greeting = yield* chat.generateText({
     prompt: "Hi! I'm learning about Effect.",
-  })
-  yield* Console.log("Assistant:", greeting.text)
+  });
+  yield* Console.log('Assistant:', greeting.text);
 
   // Second turn - the model has context from the previous message
   // This demonstrates how Chat maintains conversation state
   const followUp = yield* chat.generateText({
-    prompt: "What are the main benefits?",
-  })
-  yield* Console.log("Assistant:", followUp.text)
+    prompt: 'What are the main benefits?',
+  });
+  yield* Console.log('Assistant:', followUp.text);
 
   // Example 3: Streaming responses
-  yield* Console.log("\n=== Example 3: Streaming Text Generation ===\n")
+  yield* Console.log('\n=== Example 3: Streaming Text Generation ===\n');
 
-  yield* Console.log("Streaming response:")
+  yield* Console.log('Streaming response:');
 
   // streamText returns a Stream of response parts
   // Streams in Effect are lazy and composable
   // Stream.runForEach processes each part as it arrives
   yield* LanguageModel.streamText({
-    prompt: "Count from 1 to 5, explaining each number briefly.",
+    prompt: 'Count from 1 to 5, explaining each number briefly.',
   }).pipe(
     Stream.runForEach((part) => {
       // Only print text deltas to show streaming effect
-      if (part.type === "text-delta") {
+      if (part.type === 'text-delta') {
         // TODO: print without newlines
-        return Console.log(part.delta)
+        return Console.log(part.delta);
       }
       // Log other part types for demonstration
-      return Console.log(`[${part.type}]`)
-    })
-  )
+      return Console.log(`[${part.type}]`);
+    }),
+  );
 
-  yield* Console.log("\n=== All examples completed ===")
-})
+  yield* Console.log('\n=== All examples completed ===');
+});
 
 /**
  * Layer composition for dependency injection
@@ -98,22 +98,22 @@ const OpenRouterClientLayer = OpenRouterClient.layer({
 }).pipe(
   // Provide the Fetch HTTP client implementation
   // Layer.provide composes layers, satisfying dependencies
-  Layer.provide(FetchHttpClient.layer)
-)
+  Layer.provide(FetchHttpClient.layer),
+);
 
 // Create the language model layer using OpenRouter
 // This uses the "openai/gpt-4o-mini" model via OpenRouter
 const OpenRouterModelLayer = OpenRouterLanguageModel.layer({
-  model: "openai/gpt-4o-mini",
+  model: 'openai/gpt-4o-mini',
   config: {
     // Optional: configure model parameters
     temperature: 0.7,
     max_tokens: 500,
   },
 }).pipe(
   // The model layer depends on the OpenRouter client
-  Layer.provide(OpenRouterClientLayer)
-)
+  Layer.provide(OpenRouterClientLayer),
+);
 
 /**
  * Run the program with dependency injection
@@ -131,7 +131,7 @@ await program.pipe(
   // Provide the Bun runtime context for platform services
   Effect.provide(BunContext.layer),
   // Run the effect - returns a Promise<void>
-  Effect.runPromise
-)
+  Effect.runPromise,
+);
 
-console.log("\n✓ Program completed successfully")
+console.log('\n✓ Program completed successfully');