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name: models-and-configuration description: "Choose, configure, inspect, and troubleshoot CAMEL model backends, provider enums, config classes, local/OpenAI-compatible endpoints, ModelFactory, ModelManager, and structured output behavior." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Models and Configuration

Use this sub-skill when a task involves CAMEL model selection, provider setup, model backend construction, model config dictionaries, structured outputs, local serving endpoints, or model fallback/scheduling.

Read This First

• Start with API reference for ModelFactory, BaseModelBackend, ModelManager, ModelPlatformType, ModelType, audio model classes, and schema converters.
• Use Provider patterns to choose OpenAI, OpenAI-compatible, Ollama, vLLM, LMStudio, cloud providers, custom clients, and credential handling patterns.
• Use Configuration for camel.configs classes, model_config_dict, JSON/YAML factory configs, retries, timeouts, streaming, structured output settings, and optional extras.
• Use Troubleshooting when imports fail, API keys are missing, provider/type pairs do not match, local endpoints refuse connections, structured output parsing fails, or Python 3.13 exposes optional dependency gaps.
• Run inspect_model_registry.py to list installed CAMEL model platforms, backend classes, model enum counts, and config classes without making provider calls.

Common Entry Points

• from camel.models import ModelFactory then ModelFactory.create(...) for most chat model backends.
• from camel.types import ModelPlatformType, ModelType for provider/model enums; use a plain string model_type for local/custom model names that are not in ModelType.
• from camel.configs import ChatGPTConfig, OllamaConfig, VLLMConfig, LMStudioConfig, ... and pass ConfigClass(...).as_dict() as model_config_dict.
• Pass the model object, or a list of model objects, into camel.agents.ChatAgent(model=...); see sibling agents-and-societies for agent orchestration.
• Keep embeddings and vector retrieval in sibling memory-rag-and-data, and tool schema/runtime details in sibling tools-runtimes-and-services.

Fast Routing

• Need a cloud provider backend: read Provider patterns and Configuration.
• Need a local OpenAI-compatible endpoint: read Provider patterns.
• Need structured JSON/Pydantic output: read API reference and Troubleshooting.
• Need failover, load balancing, or model scheduling: read API reference.
• Need to know what the installed package exposes: run python scripts/inspect_model_registry.py --format text.