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bge-m3

Text Embeddings • baai
@cf/baai/bge-m3

Multi-Functionality, Multi-Linguality, and Multi-Granularity embeddings model.

Usage

Workers - TypeScript

 
export interface Env {
  AI: Ai;
}


export default {
  async fetch(request, env): Promise<Response> {


    // Can be a string or array of strings]
    const stories = [
      "This is a story about an orange cloud",
      "This is a story about a llama",
      "This is a story about a hugging emoji",
    ];


    const embeddings = await env.AI.run(
      "@cf/baai/bge-m3",
      {
        text: stories,
      }
    );


    return Response.json(embeddings);
  },
} satisfies ExportedHandler<Env>;

Python

 
import os
import requests




ACCOUNT_ID = "your-account-id"
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")


stories = [
  'This is a story about an orange cloud',
  'This is a story about a llama',
  'This is a story about a hugging emoji'
]


response = requests.post(
  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/baai/bge-m3",
  headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
  json={"text": stories}
)


print(response.json())

curl
Terminal window
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/baai/bge-m3  \
  -X POST  \
  -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN"  \
  -d '{ "text": ["This is a story about an orange cloud", "This is a story about a llama", "This is a story about a hugging emoji"] }'

Parameters

* indicates a required field

Input

  • query string min 1

    A query you wish to perform against the provided contexts. If no query is provided the model with respond with embeddings for contexts

  • contexts * array

    List of provided contexts. Note that the index in this array is important, as the response will refer to it.

    • items object

      • text string min 1

        One of the provided context content

Output

  • Query object

    • response array

      • items object

        • id integer

          Index of the context in the request

        • score number

          Score of the context under the index.

  • Embedding object

    • response array

      • items array

        • items number

API Schemas

The following schemas are based on JSON Schema

{
    "type": "object",
    "properties": {
        "query": {
            "type": "string",
            "minLength": 1,
            "description": "A query you wish to perform against the provided contexts. If no query is provided the model with respond with embeddings for contexts"
        },
        "contexts": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "text": {
                        "type": "string",
                        "minLength": 1,
                        "description": "One of the provided context content"
                    }
                }
            },
            "description": "List of provided contexts. Note that the index in this array is important, as the response will refer to it."
        }
    },
    "required": [
        "contexts"
    ]
}