Each directory (agents, hands, integrations, plugins, providers, scripts, skills) now has a README documenting its TOML format, current contents, and contribution steps.
65 lines
1.9 KiB
Markdown
65 lines
1.9 KiB
Markdown
# Providers
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LLM provider and model metadata for LibreFang. Each provider file defines the provider's API configuration and all available models with pricing, context windows, and capability flags.
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## Structure
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```
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providers/
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├── anthropic.toml
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├── openai.toml
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├── groq.toml
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└── ... (46 providers, 220+ models)
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```
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## Provider TOML Format
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```toml
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[provider]
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id = "provider-id" # Unique identifier (lowercase, hyphenated)
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display_name = "Provider Name"
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api_key_env = "PROVIDER_API_KEY" # Env var for API key
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base_url = "https://api.example.com"
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key_required = true
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[[models]]
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id = "model-id" # Exact API model ID
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display_name = "Model Name"
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tier = "smart" # frontier | smart | balanced | fast | local
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context_window = 128000
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max_output_tokens = 16384
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input_cost_per_m = 2.50 # USD per million input tokens
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output_cost_per_m = 10.0 # USD per million output tokens
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = ["short-name"]
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```
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## Tier Definitions
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| Tier | Description | Examples |
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|------|-------------|----------|
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| `frontier` | Most capable, cutting-edge | Claude Opus, GPT-4.1 |
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| `smart` | Smart, cost-effective | Claude Sonnet, Gemini 2.5 Flash |
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| `balanced` | Balanced speed/cost | GPT-4.1 Mini, Llama 3.3 70B |
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| `fast` | Fastest, cheapest | GPT-4o Mini, Claude Haiku |
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| `local` | Local models, zero cost | Ollama, vLLM, LM Studio |
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## Validation
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```bash
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python scripts/validate.py
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```
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Checks: required fields, valid tiers, non-negative costs, no duplicate model IDs.
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## Adding or Updating a Model
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1. Edit or create the provider file in `providers/`
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2. Use exact API model IDs and verify pricing from official sources
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3. Run `python scripts/validate.py`
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4. Submit a PR
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See [CONTRIBUTING.md](../CONTRIBUTING.md) for the full guide and pricing source links.
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