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model-providers

model-providers

Select and configure smolagents Model wrappers for Hugging Face Inference Providers, LiteLLM, OpenAI-compatible APIs, Azure OpenAI, Amazon Bedrock, local Transformers/MLX/vLLM, and custom Model subclasses without hardcoding credentials.

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name: model-providers description: "Select and configure smolagents Model wrappers for Hugging Face Inference Providers, LiteLLM, OpenAI-compatible APIs, Azure OpenAI, Amazon Bedrock, local Transformers/MLX/vLLM, and custom Model subclasses without hardcoding credentials." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Model Providers

Use this sub-skill when a task needs to choose, configure, debug, or serialize a smolagents model object. Agent loop design belongs in ../agent-workflows/SKILL.md; tool schemas and integrations belong in ../tools-and-integrations/SKILL.md; CLI model flags belong in ../cli-and-ui/SKILL.md; sandbox and executor choices belong in ../execution-and-safety/SKILL.md.

Fast Routing

  1. Identify the runtime: hosted API, OpenAI-compatible endpoint, Azure, Bedrock, local GPU/Apple/vLLM, or a custom adapter.
  2. Pick the wrapper from references/provider-matrix.md and install only the optional extra it needs.
  3. Read constructor details in references/api-reference.md, especially credential parameters and role/message formatting knobs.
  4. Follow setup patterns in references/workflows.md for environment variables, token limits, streaming, and agent attachment.
  5. If the config fails before generation, use references/troubleshooting.md and scripts/check_model_config.py before making live provider calls.

Common Patterns

import os
from smolagents import CodeAgent, InferenceClientModel

model = InferenceClientModel(
    model_id="Qwen/Qwen3-Next-80B-A3B-Thinking",
    provider="together",
    token=os.getenv("HF_TOKEN"),
    max_tokens=2048,
)
agent = CodeAgent(tools=[], model=model)
import os
from smolagents import OpenAIModel

model = OpenAIModel(
    model_id="gpt-4o-mini",
    api_base="https://api.openai.com/v1",
    api_key=os.getenv("OPENAI_API_KEY"),
    temperature=0.2,
)

For provider-specific unsupported parameters, pass the sentinel from smolagents.models:

from smolagents import LiteLLMModel, REMOVE_PARAMETER

model = LiteLLMModel(model_id="xai/grok-4", api_key="...", stop=REMOVE_PARAMETER)

Local Validation Helper

Run the bundled helper against a JSON or YAML model config before wiring it into an agent:

python sub-skills/model-providers/scripts/check_model_config.py model-config.json

The helper validates shape, class-specific fields, credential source references, and optional-extra hints. It does not import provider SDKs, instantiate smolagents classes, read secret values, or call network APIs.

References

  • references/provider-matrix.md maps providers and deployment styles to wrappers, extras, credentials, and caveats.
  • references/api-reference.md records constructor signatures and behavior notes.
  • references/workflows.md shows selection, environment, streaming, and custom model workflows.
  • references/troubleshooting.md covers optional imports, credentials, endpoint URLs, local memory/device failures, token limits, streaming, and custom return formatting.
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