feat(provider/azure) : enable codeInterpreter and fileSearch for AzureOpenAI

.changeset/fruity-webs-return.md

@@ -0,0 +1,6 @@
+---
+'@ai-sdk/openai': patch
+'@ai-sdk/azure': patch
+---
+
+enables code_interpreter and file_search capabilities in the Azure provider through the Responses API

content/providers/01-ai-sdk-providers/04-azure.mdx

@@ -324,6 +324,69 @@ The following OpenAI-specific metadata is returned:
 - **reasoningTokens** _number_
   The number of reasoning tokens that the model generated.
 
+#### File Search
+
+The Azure OpenAI responses API supports file search through the `azure.tools.fileSearch` tool.
+
+You can force the use of the file search tool by setting the `toolChoice` parameter to `{ type: 'tool', toolName: 'file_search' }`.
+
+```ts
+const result = await generateText({
+  model: azure.responses('gpt-5'),
+  prompt: 'What does the document say about user authentication?',
+  tools: {
+    file_search: azure.tools.fileSearch({
+      // optional configuration:
+      vectorStoreIds: ['vs_123', 'vs_456'],
+      maxNumResults: 10,
+      ranking: {
+        ranker: 'auto',
+      },
+    }),
+  },
+  // Force file search tool:
+  toolChoice: { type: 'tool', toolName: 'file_search' },
+});
+```
+
+<Note>
+  The tool must be named `file_search` when using Azure OpenAI's file search
+  functionality. This name is required by Azure OpenAI's API specification and
+  cannot be customized.
+</Note>
+
+#### Code Interpreter
+
+The Azure OpenAI responses API supports the code interpreter tool through the `azure.tools.codeInterpreter` tool. This allows models to write and execute Python code.
+
+```ts
+import { azure } from '@ai-sdk/azure';
+import { generateText } from 'ai';
+
+const result = await generateText({
+  model: azure.responses('gpt-5'),
+  prompt: 'Write and run Python code to calculate the factorial of 10',
+  tools: {
+    code_interpreter: azure.tools.codeInterpreter({
+      // optional configuration:
+      container: {
+        fileIds: ['assistant-123', 'assistant-456'], // optional file IDs to make available
+      },
+    }),
+  },
+});
+```
+
+The code interpreter tool can be configured with:
+
+- **container**: Either a container ID string or an object with `fileIds` to specify uploaded files that should be available to the code interpreter
+
+<Note>
+  The tool must be named `code_interpreter` when using Azure OpenAI's code
+  interpreter functionality. This name is required by Azure OpenAI's API
+  specification and cannot be customized.
+</Note>
+
 #### PDF support
 
 The Azure OpenAI Responses API supports reading PDF files.

examples/ai-core/src/generate-text/azure-responses-code-interpreter.ts

@@ -0,0 +1,30 @@
+import { azure } from '@ai-sdk/azure';
+import { generateText } from 'ai';
+import 'dotenv/config';
+
+/**
+ * prepare
+ * Please add parameters in your .env file for initialize Azure OpenAI..
+ * AZURE_RESOURCE_NAME="<your_resource_name>"
+ * AZURE_API_KEY="<your_api_key>"
+ */
+
+async function main() {
+  // Basic text generation
+  const basicResult = await generateText({
+    model: azure.responses('gpt-5-mini'),
+    prompt:
+      'Create a program that generates five random numbers between 1 and 100 with two decimal places, and show me the execution results.',
+    tools: {
+      code_interpreter: azure.tools.codeInterpreter({}),
+    },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  console.log(basicResult.text);
+  console.log('\n=== Other Outputs ===');
+  console.log(basicResult.toolCalls);
+  console.log(basicResult.toolResults);
+}
+
+main().catch(console.error);

examples/ai-core/src/generate-text/azure-responses-file-search.ts

@@ -0,0 +1,44 @@
+import { azure } from '@ai-sdk/azure';
+import { generateText } from 'ai';
+import 'dotenv/config';
+
+/**
+ * prepare 1
+ * Please add parameters in your .env file for initialize Azure OpenAI.
+ * AZURE_RESOURCE_NAME="<your_resource_name>"
+ * AZURE_API_KEY="<your_api_key>"
+ *
+ * prepare 2
+ * Please create vector store and put file in your vector.
+ * URL:AOAI vector store portal
+ * https://oai.azure.com/resource/vectorstore
+ */
+
+const VectorStoreId = 'vs_xxxxxxxxxxxxxxxxxxxxxxxx'; // put your vector store id.
+
+async function main() {
+  // Basic text generation
+  const basicResult = await generateText({
+    model: azure.responses('gpt-4.1-mini'),
+    prompt: 'What is quantum computing?', // please question about your documents.
+    tools: {
+      file_search: azure.tools.fileSearch({
+        // optional configuration:
+        vectorStoreIds: [VectorStoreId],
+        maxNumResults: 10,
+        ranking: {
+          ranker: 'auto',
+        },
+      }),
+    },
+    // Force file search tool:
+    toolChoice: { type: 'tool', toolName: 'file_search' },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  console.log(basicResult.text);
+  console.log(basicResult.toolCalls);
+  console.log(basicResult.toolResults);
+}
+
+main().catch(console.error);

examples/ai-core/src/generate-text/openai-responses-code-interpreter.ts

@@ -0,0 +1,23 @@
+import { openai } from '@ai-sdk/openai';
+import { generateText } from 'ai';
+import 'dotenv/config';
+
+async function main() {
+  // Basic text generation
+  const basicResult = await generateText({
+    model: openai.responses('gpt-4.1-mini'),
+    prompt:
+      'Create a program that generates five random numbers between 1 and 100 with two decimal places, and show me the execution results.',
+    tools: {
+      code_interpreter: openai.tools.codeInterpreter({}),
+    },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  console.log(basicResult.text);
+  console.log('\n=== Other Outputs ===');
+  console.log(basicResult.toolCalls);
+  console.log(basicResult.toolResults);
+}
+
+main().catch(console.error);

examples/ai-core/src/generate-text/openai-responses-file-search.ts

@@ -0,0 +1,39 @@
+import { openai } from '@ai-sdk/openai';
+import { generateText } from 'ai';
+import 'dotenv/config';
+
+/**
+ * prepare
+ * Please create vector store and put file in your vector.
+ * URL:openai vector store dashboard
+ * https://platform.openai.com/storage/vector_stores/
+ */
+
+const VectorStoreId = 'vs_xxxxxxxxxxxxxxxxxxxxxxxx'; // put your vector store id.
+
+async function main() {
+  // Basic text generation
+  const basicResult = await generateText({
+    model: openai.responses('gpt-4.1-mini'),
+    prompt: 'What is quantum computing?', // please question about your documents.
+    tools: {
+      file_search: openai.tools.fileSearch({
+        // optional configuration:
+        vectorStoreIds: [VectorStoreId],
+        maxNumResults: 10,
+        ranking: {
+          ranker: 'auto',
+        },
+      }),
+    },
+    // Force file search tool:
+    toolChoice: { type: 'tool', toolName: 'file_search' },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  console.log(basicResult.text);
+  console.dir(basicResult.toolCalls, { depth: null });
+  console.dir(basicResult.toolResults, { depth: null });
+}
+
+main().catch(console.error);

examples/ai-core/src/stream-text/azure-responses-code-interpreter.ts

@@ -0,0 +1,32 @@
+import { azure } from '@ai-sdk/azure';
+import { streamText } from 'ai';
+import 'dotenv/config';
+
+/**
+ * prepare
+ * Please add parameters in your .env file for initialize Azure OpenAI..
+ * AZURE_RESOURCE_NAME="<your_resource_name>"
+ * AZURE_API_KEY="<your_api_key>"
+ */
+
+async function main() {
+  // Basic text generation
+  const result = streamText({
+    model: azure.responses('gpt-5-mini'),
+    prompt:
+      'Create a program that generates five random numbers between 1 and 100 with two decimal places, and show me the execution results.',
+    tools: {
+      code_interpreter: azure.tools.codeInterpreter({}),
+    },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  for await (const textPart of result.textStream) {
+    process.stdout.write(textPart);
+  }
+  console.log('\n=== Other Outputs ===');
+  console.log(await result.toolCalls);
+  console.log(await result.toolResults);
+}
+
+main().catch(console.error);

examples/ai-core/src/stream-text/azure-responses-file-search.ts

@@ -0,0 +1,48 @@
+import { azure } from '@ai-sdk/azure';
+import { streamText } from 'ai';
+import 'dotenv/config';
+
+/**
+ * prepare 1
+ * Please add parameters in your .env file for initialize Azure OpenAI.
+ * AZURE_RESOURCE_NAME="<your_resource_name>"
+ * AZURE_API_KEY="<your_api_key>"
+ *
+ * prepare 2
+ * Please create vector store and put file in your vector.
+ * URL:AOAI vector store portal
+ * https://oai.azure.com/resource/vectorstore
+ */
+
+const VectorStoreId = 'vs_xxxxxxxxxxxxxxxxxxxxxxxx'; // put your vector store id.
+
+async function main() {
+  // Basic text generation
+  const result = await streamText({
+    model: azure.responses('gpt-4.1-mini'),
+    prompt: 'What is quantum computing?', // please question about your documents.
+    tools: {
+      file_search: azure.tools.fileSearch({
+        // optional configuration:
+        vectorStoreIds: [VectorStoreId],
+        maxNumResults: 10,
+        ranking: {
+          ranker: 'auto',
+        },
+      }),
+    },
+    // Force file search tool:
+    toolChoice: { type: 'tool', toolName: 'file_search' },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  for await (const textPart of result.textStream) {
+    process.stdout.write(textPart);
+  }
+  console.log('\n=== Other Outputs ===');
+  console.dir(await result.toolCalls, { depth: Infinity });
+  console.dir(await result.toolResults, { depth: Infinity });
+  console.dir(await result.sources, { depth: Infinity });
+}
+
+main().catch(console.error);

examples/ai-core/src/stream-text/openai-responses-code-interpreter.ts

@@ -0,0 +1,25 @@
+import { openai } from '@ai-sdk/openai';
+import { streamText } from 'ai';
+import 'dotenv/config';
+
+async function main() {
+  // Basic text generation
+  const result = streamText({
+    model: openai.responses('gpt-4.1-mini'),
+    prompt:
+      'Create a program that generates five random numbers between 1 and 100 with two decimal places, and show me the execution results.',
+    tools: {
+      code_interpreter: openai.tools.codeInterpreter({}),
+    },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  for await (const textPart of result.textStream) {
+    process.stdout.write(textPart);
+  }
+  console.log('\n=== Other Outputs ===');
+  console.log(await result.toolCalls);
+  console.log(await result.toolResults);
+}
+
+main().catch(console.error);

examples/ai-core/src/stream-text/openai-responses-file-search.ts

@@ -0,0 +1,42 @@
+import { openai } from '@ai-sdk/openai';
+import { streamText } from 'ai';
+import 'dotenv/config';
+
+/**
+ * prepare
+ * Please create vector store and put file in your vector.
+ * URL:openai vector store dashboard
+ * https://platform.openai.com/storage/vector_stores/
+ */
+
+const VectorStoreId = 'vs_xxxxxxxxxxxxxxxxxxxxxxxx'; // put your vector store id.
+
+async function main() {
+  // Basic text generation
+  const result = await streamText({
+    model: openai.responses('gpt-4.1-mini'),
+    prompt: 'What is quantum computing?', // please question about your documents.
+    tools: {
+      file_search: openai.tools.fileSearch({
+        // optional configuration:
+        vectorStoreIds: [VectorStoreId],
+        maxNumResults: 10,
+        ranking: {
+          ranker: 'auto',
+        },
+      }),
+    },
+    // Force file search tool:
+    toolChoice: { type: 'tool', toolName: 'file_search' },
+  });
+
+  console.log('\n=== Basic Text Generation ===');
+  for await (const textPart of result.textStream) {
+    process.stdout.write(textPart);
+  }
+  console.log('\n=== Other Outputs ===');
+  console.dir(await result.toolCalls, { depth: null });
+  console.dir(await result.toolResults, { depth: null });
+}
+
+main().catch(console.error);