Model Providers

Fabric Harness uses an explicit provider/model-id reference everywhere a model is selected. There is no implicit "default OpenAI" — you opt into a provider by configuring credentials and naming the model.

Reference format

provider/model-id

Examples:

openai/gpt-5.5
openai/gpt-5.5
openai/gpt-5.5
mock/test-model

Setting credentials

Put provider keys once in a repo/workspace .env.local; Fabric Harness auto-loads .env and .env.local files, while shell env still wins:

cp .env.example .env.local
# OPENAI_API_KEY=...
# ANTHROPIC_API_KEY=...
# AZURE_OPENAI_ENDPOINT=https://....openai.azure.com
# AZURE_OPENAI_API_KEY=...

Use explicit --env <file> only for overrides. Never paste API keys into source files or session artifacts.

Selecting the model

The first non-empty wins, in this order:

1. CLI flag: fh run ask --model openai/gpt-5.5
2. Environment: FABRIC_MODEL=openai/gpt-5.5
3. .fabricharness/config.ts → run.model or agent.model
4. Agent-declared default: agent({ model: 'openai/gpt-5.5' })

Per-call override:

await session.prompt('Summarize', { model: 'openai/gpt-5.5' });

Mock provider

For local development and tests, mock/test-model returns deterministic stub responses. It honors the typed-result schema where possible.

export default agent({
  // ...
  model: process.env.FABRIC_MODEL ?? 'mock/test-model',
});

Provider env names

Fabric Harness knows the standard env names for common providers:

• OPENAI_API_KEY
• ANTHROPIC_API_KEY
• OPENROUTER_API_KEY
• GEMINI_API_KEY
• GOOGLE_API_KEY
• AZURE_OPENAI_API_KEY + AZURE_OPENAI_ENDPOINT
• GROQ_API_KEY
• MISTRAL_API_KEY
• COHERE_API_KEY

Roadmap

• Foundry-runtime model routing for hosted-agent deployments.
• Per-call cost telemetry (today: token usage in fh metrics).