This provider enables model management for Cloudflare AI Gateway, which acts as a unified proxy for multiple AI providers (OpenAI, Anthropic, Workers AI, Replicate, etc.).

Overview

Cloudflare AI Gateway provides a compatibility layer that allows you to access models from various providers through a single endpoint. This provider automatically fetches available models from the Cloudflare API and generates TOML configuration files for use in the models.dev system.

Directory Structure

cloudflare-ai-gateway/
├── data/
│   ├── api_response.json    # Cached API response from Cloudflare
│   └── model_names.json     # Human-readable name mappings
├── models/                   # Generated TOML files
│   ├── anthropic/
│   ├── openai/
│   ├── replicate/
│   └── workers-ai/
├── scripts/
│   ├── 01_fetch_model_data.sh      # Fetches models from Cloudflare API
│   ├── 02_generate_model_names.sh  # Updates model name mappings
│   ├── 03_generate_model_toml.sh   # Generates TOML files
│   └── utils.sh                     # Shared utility functions
├── provider.toml            # Provider configuration
└── README.md                # This file

How It Works

1. Model Fetching (01_fetch_model_data.sh)

This script fetches the list of available models from the Cloudflare AI Gateway API:

API Endpoint: https://gateway.ai.cloudflare.com/v1/{ACCOUNT_ID}/{GATEWAY_ID}/compat/models
Authentication: Uses CLOUDFLARE_API_TOKEN for authorization
Output: Saves the API response to data/api_response.json

The API returns model data including:

Model ID (e.g., openai/gpt-4o, anthropic/claude-3.5-sonnet)
Cost per token (input and output)
Creation timestamp
Other metadata

2. Model Name Generation (02_generate_model_names.sh)

This script manages the data/model_names.json file, which maps model IDs to human-readable names:

Reads from data/api_response.json
Adds new model IDs to model_names.json (if not already present)
Preserves existing name mappings
Filters models based on configuration in utils.sh

Model Filtering:

Includes ALL models from: workers-ai, replicate
Includes ONLY well-known models from: openai, anthropic
Skips namespaces: replicate/replicate-internal
Skips specific models: aura-1, whisper

3. TOML Generation (03_generate_model_toml.sh)

This script generates TOML configuration files for each model:

Two Generation Strategies:

Cross-referencing (for OpenAI and Anthropic):
- Copies TOML files from the source provider directories
- Maps Cloudflare model names to canonical provider names
- Example: anthropic/claude-3.5-sonnet → ../../anthropic/models/claude-3-5-sonnet-20241022.toml
Auto-generation (for Workers AI and Replicate):
- Generates TOML files with default values
- Uses cost and metadata from the API response
- Converts cost per token → cost per million tokens
- Sets default capabilities (context length, modalities, etc.)

Generated TOML Structure:

name = "Model Name"
release_date = "2024-01-01"
last_updated = "2024-01-01"
attachment = false
reasoning = false
temperature = true
tool_call = false
open_weights = false

[cost]
input = 0.15      # USD per 1M input tokens
output = 0.60     # USD per 1M output tokens

[limit]
context = 128000   # Max context tokens
output = 16384     # Max output tokens

[modalities]
input = ["text"]
output = ["text"]

4. Utilities (utils.sh)

Shared configuration and helper functions:

Configuration:

INCLUDE_ALL_PROVIDERS: Providers to include all models from
CROSS_REFERENCE_PROVIDERS: Providers to copy from source directories
WELL_KNOWN_MODELS: Regex patterns for specific models to include
SKIP_NAMESPACES: Namespaces to exclude
SKIP_MODELS: Specific models to exclude

Helper Functions:

should_include_model(): Determines if a model should be included
get_mapped_name(): Maps Cloudflare names to source provider names
find_source_file(): Locates source TOML files for cross-referencing

Usage

Prerequisites

Cloudflare account with AI Gateway configured
Required environment variables:
- CLOUDFLARE_API_TOKEN: Your Cloudflare API token
- CLOUDFLARE_ACCOUNT_ID: Your Cloudflare account ID
- CLOUDFLARE_GATEWAY_ID: Your AI Gateway name/ID

Running the Scripts

Run scripts individually or in sequence:

# Step 1: Fetch model data from Cloudflare API
cd scripts
CLOUDFLARE_API_TOKEN=xxx \
CLOUDFLARE_ACCOUNT_ID=xxx \
CLOUDFLARE_GATEWAY_ID=xxx \
./01_fetch_model_data.sh

# Step 2: Update model name mappings
./02_generate_model_names.sh

# Step 3: Generate TOML files
./03_generate_model_toml.sh

Configuration

Edit scripts/utils.sh to customize:

Add a provider to include all models:

INCLUDE_ALL_PROVIDERS="workers-ai replicate my-new-provider"

Add a well-known model:

WELL_KNOWN_MODELS=(
  # ... existing patterns ...
  "openai/gpt-5$"
)

Skip a namespace:

SKIP_NAMESPACES="replicate/replicate-internal my-provider/internal"

Cross-reference a provider:

CROSS_REFERENCE_PROVIDERS="openai anthropic google"

Model Name Mappings

Edit data/model_names.json to provide human-readable names:

{
  "workers-ai/llama-3-8b-instruct": "Llama 3 8B Instruct",
  "openai/gpt-4o": "GPT-4o",
  "anthropic/claude-3.5-sonnet": "Claude 3.5 Sonnet"
}

Model ID Format

Cloudflare uses BOTH dots and hyphens in model IDs (the API returns both formats):

OpenAI: openai/gpt-5.1 OR openai/gpt-5-1, openai/gpt-3.5-turbo OR openai/gpt-3-5-turbo
Anthropic: anthropic/claude-3.5-sonnet OR anthropic/claude-3-5-sonnet, anthropic/claude-haiku-4-5
Workers AI: workers-ai/@cf/meta/llama-3-8b-instruct
Replicate: replicate/meta/meta-llama-3-70b-instruct

Important: The API returns duplicate models with different naming conventions (dots vs hyphens). The WELL_KNOWN_MODELS patterns handle both formats using [\.-] regex to match either a dot or hyphen.

File Path Conversion:

Dots are preserved in filenames: openai/gpt-5.1.toml
Workers AI special handling: workers-ai/@cf/meta/llama → workers-ai/llama.toml

Cross-Referencing Logic

For OpenAI and Anthropic models, the scripts map Cloudflare model IDs to canonical provider filenames:

Anthropic Mappings:

claude-3.5-sonnet → claude-3-5-sonnet-20241022.toml
claude-3.5-haiku → claude-3-5-haiku-latest.toml
claude-3-opus → claude-3-opus-20240229.toml

OpenAI Mappings:

gpt-5.1 → gpt-5.1.toml
gpt-3.5-turbo → gpt-3.5-turbo.toml

This ensures consistency with the canonical provider definitions while supporting Cloudflare's naming conventions.

Cleanup

The TOML generation script automatically:

Removes models that are no longer in the API response
Cleans up empty directories
Maintains a clean models directory

Troubleshooting

API errors:

Verify environment variables are set correctly
Check API token has necessary permissions
Ensure Gateway ID matches your Cloudflare configuration

Missing models:

Check if the model is filtered by utils.sh configuration
Review WELL_KNOWN_MODELS patterns
Verify the model exists in data/api_response.json

Cross-referencing failures:

Ensure source provider directories exist (e.g., ../openai/models/)
Check model name mappings in get_mapped_name()
Verify source TOML files exist with correct names

Provider Configuration

The provider.toml file defines how OpenCode connects to Cloudflare AI Gateway:

name = "Cloudflare AI Gateway"
env = ["CLOUDFLARE_API_TOKEN", "CLOUDFLARE_ACCOUNT_ID", "CLOUDFLARE_GATEWAY_ID"]
npm = "@ai-sdk/openai-compatible"
api = "https://gateway.ai.cloudflare.com/v1/${CLOUDFLARE_ACCOUNT_ID}/${CLOUDFLARE_GATEWAY_ID}/compat/"
doc = "https://developers.cloudflare.com/ai-gateway/"

README.md

Cloudflare AI Gateway Provider