Middleware Implementation

Middleware allows you to enhance the behavior of language models by intercepting and modifying calls. You can implement custom middleware for logging, caching, guardrails, RAG, and more.

Implementing middleware requires understanding of the language model specification.

Middleware Specification

Middleware implements the LanguageModelV3Middleware interface:

import type { LanguageModelV3Middleware } from '@ai-sdk/provider';

export const myMiddleware: LanguageModelV3Middleware = {
  specificationVersion: 'v3',
  transformParams: async ({ params }) => {
    // Transform parameters before they reach the model
    return params;
  },
  wrapGenerate: async ({ doGenerate, params }) => {
    // Wrap the doGenerate method
    const result = await doGenerate();
    return result;
  },
  wrapStream: async ({ doStream, params }) => {
    // Wrap the doStream method
    const result = await doStream();
    return result;
  },
};

Middleware Methods

transformParams

Transforms parameters before they’re passed to the model:

import type {
  LanguageModelV3Middleware,
  LanguageModelV3CallOptions,
} from '@ai-sdk/provider';

export const parameterMiddleware: LanguageModelV3Middleware = {
  specificationVersion: 'v3',
  transformParams: async ({ params }) => {
    // Add a system message
    return {
      ...params,
      prompt: {
        ...params.prompt,
        messages: [
          {
            role: 'system',
            content: 'You are a helpful assistant.',
          },
          ...params.prompt.messages,
        ],
      },
    } as LanguageModelV3CallOptions;
  },
};

wrapGenerate

Wraps the doGenerate method for non-streaming calls:

import type { LanguageModelV3Middleware } from '@ai-sdk/provider';

export const generateMiddleware: LanguageModelV3Middleware = {
  specificationVersion: 'v3',
  wrapGenerate: async ({ doGenerate, params }) => {
    console.log('Generate called with:', params.prompt);

    const startTime = Date.now();
    const result = await doGenerate();
    const duration = Date.now() - startTime;

    console.log('Generate completed in', duration, 'ms');
    console.log('Generated text:', result.text);

    return result;
  },
};

wrapStream

Wraps the doStream method for streaming calls:

import type {
  LanguageModelV3Middleware,
  LanguageModelV3StreamPart,
} from '@ai-sdk/provider';

export const streamMiddleware: LanguageModelV3Middleware = {
  specificationVersion: 'v3',
  wrapStream: async ({ doStream, params }) => {
    const { stream, ...rest } = await doStream();

    let fullText = '';

    const transformStream = new TransformStream<
      LanguageModelV3StreamPart,
      LanguageModelV3StreamPart
    >({
      transform(chunk, controller) {
        if (chunk.type === 'text-delta') {
          fullText += chunk.textDelta;
        }
        controller.enqueue(chunk);
      },
      flush() {
        console.log('Stream complete. Full text:', fullText);
      },
    });

    return {
      stream: stream.pipeThrough(transformStream),
      ...rest,
    };
  },
};

Real-World Middleware Examples

Logging Middleware

Log all model interactions:

import type {
  LanguageModelV3Middleware,
  LanguageModelV3StreamPart,
} from '@ai-sdk/provider';

export const loggingMiddleware: LanguageModelV3Middleware = {
  specificationVersion: 'v3',
  wrapGenerate: async ({ doGenerate, params }) => {
    const requestId = crypto.randomUUID();
    console.log(`[${requestId}] Generate request:`, {
      messages: params.prompt.messages.length,
      maxTokens: params.maxOutputTokens,
    });

    const startTime = Date.now();
    try {
      const result = await doGenerate();
      const duration = Date.now() - startTime;

      console.log(`[${requestId}] Generate response:`, {
        duration,
        tokens: result.usage,
        finishReason: result.finishReason,
      });

      return result;
    } catch (error) {
      console.error(`[${requestId}] Generate error:`, error);
      throw error;
    }
  },

  wrapStream: async ({ doStream, params }) => {
    const requestId = crypto.randomUUID();
    console.log(`[${requestId}] Stream request:`, {
      messages: params.prompt.messages.length,
    });

    const { stream, ...rest } = await doStream();
    let chunkCount = 0;

    const transformStream = new TransformStream<
      LanguageModelV3StreamPart,
      LanguageModelV3StreamPart
    >({
      transform(chunk, controller) {
        chunkCount++;
        controller.enqueue(chunk);
      },
      flush() {
        console.log(`[${requestId}] Stream complete:`, { chunks: chunkCount });
      },
    });

    return {
      stream: stream.pipeThrough(transformStream),
      ...rest,
    };
  },
};

Caching Middleware

Cache model responses:

import type { LanguageModelV3Middleware } from '@ai-sdk/provider';

interface CacheEntry {
  result: any;
  timestamp: number;
}

export function createCachingMiddleware({
  ttl = 3600000, // 1 hour
}: {
  ttl?: number;
} = {}): LanguageModelV3Middleware {
  const cache = new Map<string, CacheEntry>();

  const getCacheKey = (params: any): string => {
    return JSON.stringify({
      messages: params.prompt.messages,
      settings: {
        temperature: params.temperature,
        maxTokens: params.maxOutputTokens,
      },
    });
  };

  return {
    specificationVersion: 'v3',
    wrapGenerate: async ({ doGenerate, params }) => {
      const cacheKey = getCacheKey(params);
      const cached = cache.get(cacheKey);

      if (cached && Date.now() - cached.timestamp < ttl) {
        console.log('Cache hit:', cacheKey.slice(0, 50));
        return cached.result;
      }

      const result = await doGenerate();

      cache.set(cacheKey, {
        result,
        timestamp: Date.now(),
      });

      // Clean up old entries
      for (const [key, entry] of cache.entries()) {
        if (Date.now() - entry.timestamp > ttl) {
          cache.delete(key);
        }
      }

      return result;
    },
  };
}

RAG Middleware

Add context from a vector database:

import type { LanguageModelV3Middleware } from '@ai-sdk/provider';

export function createRAGMiddleware({
  retrieveContext,
}: {
  retrieveContext: (query: string) => Promise<string[]>;
}): LanguageModelV3Middleware {
  return {
    specificationVersion: 'v3',
    transformParams: async ({ params }) => {
      // Get the last user message
      const messages = params.prompt.messages;
      const lastMessage = messages[messages.length - 1];

      if (lastMessage?.role !== 'user') {
        return params;
      }

      // Extract text from user message
      const userText =
        typeof lastMessage.content === 'string'
          ? lastMessage.content
          : lastMessage.content
              .filter((part: any) => part.type === 'text')
              .map((part: any) => part.text)
              .join(' ');

      // Retrieve context
      const contextChunks = await retrieveContext(userText);

      if (contextChunks.length === 0) {
        return params;
      }

      // Add context to the message
      const contextText =
        '\n\nRelevant context:\n' + contextChunks.join('\n\n');

      const enhancedContent =
        typeof lastMessage.content === 'string'
          ? lastMessage.content + contextText
          : [
              ...lastMessage.content,
              { type: 'text', text: contextText },
            ];

      return {
        ...params,
        prompt: {
          ...params.prompt,
          messages: [
            ...messages.slice(0, -1),
            {
              ...lastMessage,
              content: enhancedContent,
            },
          ],
        },
      };
    },
  };
}

Guardrail Middleware

Filter sensitive information:

import type {
  LanguageModelV3Middleware,
  LanguageModelV3StreamPart,
} from '@ai-sdk/provider';

export function createGuardrailMiddleware({
  filters,
}: {
  filters: Array<{
    pattern: RegExp;
    replacement: string;
  }>;
}): LanguageModelV3Middleware {
  const applyFilters = (text: string): string => {
    let filtered = text;
    for (const { pattern, replacement } of filters) {
      filtered = filtered.replace(pattern, replacement);
    }
    return filtered;
  };

  return {
    specificationVersion: 'v3',
    wrapGenerate: async ({ doGenerate }) => {
      const result = await doGenerate();
      return {
        ...result,
        text: result.text ? applyFilters(result.text) : undefined,
      };
    },

    wrapStream: async ({ doStream }) => {
      const { stream, ...rest } = await doStream();

      const transformStream = new TransformStream<
        LanguageModelV3StreamPart,
        LanguageModelV3StreamPart
      >({
        transform(chunk, controller) {
          if (chunk.type === 'text-delta') {
            controller.enqueue({
              ...chunk,
              textDelta: applyFilters(chunk.textDelta),
            });
          } else {
            controller.enqueue(chunk);
          }
        },
      });

      return {
        stream: stream.pipeThrough(transformStream),
        ...rest,
      };
    },
  };
}

// Usage
const model = wrapLanguageModel({
  model: openai('gpt-4'),
  middleware: createGuardrailMiddleware({
    filters: [
      { pattern: /\b\d{3}-\d{2}-\d{4}\b/g, replacement: '[SSN REDACTED]' },
      { pattern: /\b[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,}\b/gi, replacement: '[EMAIL REDACTED]' },
    ],
  }),
});

Retry Middleware

Add custom retry logic:

import type { LanguageModelV3Middleware } from '@ai-sdk/provider';

export function createRetryMiddleware({
  maxRetries = 3,
  delay = 1000,
}: {
  maxRetries?: number;
  delay?: number;
} = {}): LanguageModelV3Middleware {
  const retry = async <T>(
    fn: () => Promise<T>,
    attempt = 1,
  ): Promise<T> => {
    try {
      return await fn();
    } catch (error) {
      if (attempt >= maxRetries) {
        throw error;
      }
      await new Promise(resolve => setTimeout(resolve, delay * attempt));
      return retry(fn, attempt + 1);
    }
  };

  return {
    specificationVersion: 'v3',
    wrapGenerate: async ({ doGenerate }) => {
      return retry(() => doGenerate());
    },
    wrapStream: async ({ doStream }) => {
      return retry(() => doStream());
    },
  };
}

Composing Middleware

Combine multiple middleware:

import { wrapLanguageModel } from 'ai';
import { openai } from '@ai-sdk/openai';

const model = wrapLanguageModel({
  model: openai('gpt-4'),
  middleware: [
    loggingMiddleware,
    createCachingMiddleware({ ttl: 3600000 }),
    createRAGMiddleware({ retrieveContext }),
    createGuardrailMiddleware({ filters }),
  ],
});

// Applied as: logging(caching(rag(guardrail(model))))

Accessing Provider Metadata

Pass custom metadata to middleware:

import { generateText, wrapLanguageModel } from 'ai';
import { openai } from '@ai-sdk/openai';
import type { LanguageModelV3Middleware } from '@ai-sdk/provider';

export const metadataMiddleware: LanguageModelV3Middleware = {
  specificationVersion: 'v3',
  wrapGenerate: async ({ doGenerate, params }) => {
    const metadata = params?.providerMetadata?.myMiddleware;
    console.log('Request metadata:', metadata);
    return doGenerate();
  },
};

const { text } = await generateText({
  model: wrapLanguageModel({
    model: openai('gpt-4'),
    middleware: metadataMiddleware,
  }),
  prompt: 'Hello',
  providerOptions: {
    myMiddleware: {
      userId: '12345',
      requestId: 'abc-def',
    },
  },
});

Testing Middleware

import { describe, it, expect, vi } from 'vitest';
import { generateText, wrapLanguageModel } from 'ai';
import { createMockLanguageModelV3 } from 'ai/test';

describe('Logging Middleware', () => {
  it('should log requests and responses', async () => {
    const consoleLogSpy = vi.spyOn(console, 'log');

    const mockModel = createMockLanguageModelV3({
      doGenerate: async () => ({
        text: 'Hello!',
        finishReason: 'stop',
        usage: { inputTokens: 10, outputTokens: 5 },
      }),
    });

    const model = wrapLanguageModel({
      model: mockModel,
      middleware: loggingMiddleware,
    });

    await generateText({
      model,
      prompt: 'Hi',
    });

    expect(consoleLogSpy).toHaveBeenCalled();
  });
});

Best Practices

Always handle both generate and stream: Implement both wrapGenerate and wrapStream for consistent behavior
Preserve stream characteristics: Don’t buffer entire streams in memory
Handle errors gracefully: Wrap operations in try-catch blocks
Document side effects: Clearly document any caching, logging, or external calls
Make middleware configurable: Accept options for customization
Test thoroughly: Test both success and error paths

Next Steps

Learn about error recovery strategies
Explore custom providers
Review built-in middleware

Getting Started

Foundations

AI SDK Core

Agents

AI SDK UI

AI SDK RSC

Advanced

Troubleshooting

Middleware Implementation

Middleware Implementation

Middleware Specification

Middleware Methods

transformParams

wrapGenerate

wrapStream

Real-World Middleware Examples

Logging Middleware

Caching Middleware

RAG Middleware

Guardrail Middleware

Retry Middleware

Composing Middleware

Accessing Provider Metadata

Testing Middleware

Best Practices

Next Steps

Getting Started

Foundations

AI SDK Core

Agents

AI SDK UI

AI SDK RSC

Advanced

Troubleshooting

​Middleware Implementation

​Middleware Specification

​Middleware Methods

​transformParams

​wrapGenerate

​wrapStream

​Real-World Middleware Examples

​Logging Middleware

​Caching Middleware

​RAG Middleware

​Guardrail Middleware

​Retry Middleware

​Composing Middleware

​Accessing Provider Metadata

​Testing Middleware

​Best Practices

​Next Steps

Middleware Implementation

Middleware Specification

Middleware Methods

transformParams

wrapGenerate

wrapStream

Real-World Middleware Examples

Logging Middleware

Caching Middleware

RAG Middleware

Guardrail Middleware

Retry Middleware

Composing Middleware

Accessing Provider Metadata

Testing Middleware

Best Practices

Next Steps