feat(ai-gateway-provider): add embedding model support

[agcty]

Summary

Adds embedding model support to ai-gateway-provider, allowing users to route embedding requests through AI Gateway.

Changes

• Add AiGatewayEmbeddingModel class implementing EmbeddingModelV3
• Add embedding(), textEmbedding(), and textEmbeddingModel() methods to the provider factory
• Extract shared types and utilities to shared.ts to avoid circular imports
• Add comprehensive test coverage for embedding functionality

Usage

import { createAiGateway } from "ai-gateway-provider";
import { createOpenAI } from "@ai-sdk/openai";
import { embed } from "ai";

const gateway = createAiGateway({
  accountId: "your-account-id",
  gateway: "your-gateway",
  apiKey: "your-api-key",
});

const openai = createOpenAI({ apiKey: "..." });

const { embedding } = await embed({
  model: gateway.embedding(openai.textEmbeddingModel("text-embedding-3-small")),
  value: "Hello, world!",
});

Test plan

• All existing tests pass (13 tests)
• New embedding tests pass (6 tests)
• Type checking passes
• Changeset included

🤖 Generated with Claude Code

[changeset-bot]

🦋 Changeset detected

Latest commit: 7c03126

The changes in this PR will be included in the next version bump.

This PR includes changesets to release 1 package

Name	Type
ai-gateway-provider	Minor

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[agcty]

Testing Notes

I tested this implementation locally by routing Google embedding requests through AI Gateway. The routing works correctly - requests are intercepted, reformatted for the Universal Endpoint, and return successful responses.

Debug logs from local testing (not included in final code):

[ai-gateway-embedding] doEmbed called, models: 1
[ai-gateway-embedding] Processing model: google.generative-ai gemini-embedding-001
[ai-gateway-embedding] FETCH INTERCEPTED: https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-001:embedContent
[ai-gateway-embedding] Requests captured: 1
[ai-gateway-embedding] Request body: [
  {
    "endpoint": "v1beta/models/gemini-embedding-001:embedContent",
    "headers": {
      "content-type": "application/json",
      "x-goog-api-key": "..."
    },
    "provider": "google-ai-studio",
    "query": {
      "model": "models/gemini-embedding-001",
      "content": { "parts": [{ "text": "..." }] },
      "outputDimensionality": 1024
    }
  }
]
[ai-gateway-embedding] Sending to AI Gateway: https://gateway.ai.cloudflare.com/v1/{accountId}/test
[ai-gateway-embedding] AI Gateway response status: 200

Note: Embedding requests don't appear in the AI Gateway dashboard, though they route correctly and return 200 responses. This may require backend support to display embedding analytics alongside chat completions.

[agcty]

@threepointone Hey! Not sure who the right person to tag is, but I'd love to get your thoughts on this.
It would be great to record token usage for embeddings via AI Gateway. I'm not sure what work this would require on the Cloudflare side, if it's not something that can be supported, we can explore other options. Just wanted to check if this is a feature CF would be interested in supporting.

[threepointone]

@palashgo what do you think