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Copy file name to clipboardExpand all lines: docs/configuration.md
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## Global Configuration (`RubyLLM.configure`)
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> Coming in v1.3.0
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> OpenRouter support is coming in v1.3.0
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The primary way to configure RubyLLM is using the `RubyLLM.configure` block. This typically runs once when your application starts (e.g., in `config/initializers/ruby_llm.rb` for Rails apps, or at the top of a script).
# Uses standard AWS credential chain (environment, shared config, IAM role)
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*`anthropic_api_key`
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*`gemini_api_key`
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*`deepseek_api_key`
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*`openrouter_api_key`
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*`bedrock_api_key`, `bedrock_secret_key`, `bedrock_region`, `bedrock_session_token` (See AWS documentation for standard credential methods if not set explicitly).
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## Custom OpenAI API Base (`openai_api_base`)
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## Scoped Configuration with Contexts
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New (v1.3.0)
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Coming in v1.3.0
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While `RubyLLM.configure` sets global defaults, `RubyLLM.context` allows you to create temporary, isolated configuration scopes for specific API calls. This is ideal for situations requiring different keys, endpoints, or timeouts temporarily without affecting the rest of the application.
Copy file name to clipboardExpand all lines: docs/guides/models.md
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# Working with AI Models
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RubyLLM provides a unified interface to a wide array of AI models from different providers like OpenAI, Anthropic, Google, AWS Bedrock, and DeepSeek. This guide covers how RubyLLM discovers, manages, and allows you to interact with these models, including advanced scenarios like custom endpoints.
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RubyLLM provides a unified interface to a wide array of AI models from different providers like OpenAI, Anthropic, Google, AWS Bedrock, OpenRouter and DeepSeek. This guide covers how RubyLLM discovers, manages, and allows you to interact with these models, including advanced scenarios like custom endpoints.
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