AWS Bedrock Integration
Added first-class support for provider = "bedrock" using AWS SigV4 request signing and the Bedrock Converse API. New AWS parameters in call_llm() include aws_region, aws_access_key_id, aws_secret_access_key, and aws_session_token.
Azure OpenAI Integration
Added provider = "azure_openai" with deployment-based endpoint routing and api-key authentication. New Azure OpenAI parameters in call_llm() include azure_endpoint and azure_api_version.
Azure AI Foundry Integration
Added provider = "azure_foundry" with support for either api-key or bearer token authentication. New Foundry parameters in call_llm() include azure_foundry_endpoint, azure_foundry_api_version, and azure_foundry_token.
Model Catalog Expansion
list_models() now supports both Azure providers and Bedrock. list_models("all") includes the expanded provider set.
Provider-specific guidance Error messages now provide more precise credential hints for AWS Bedrock, Azure OpenAI, and Azure AI Foundry.
Tests and documentation Added test coverage for Bedrock, Azure OpenAI, and Azure AI Foundry provider paths, and updated generated Rd documentation accordingly.
Google Gemini Integration
chat_llm() now speaks to Gemini via Google’s OpenAI-compatible Chat Completions API (…/v1beta/openai/chat/completions). The default model is gemini-2.0-flash, and new helpers (get_gemini_models(), "gemini" option in list_models()) make catalog discovery a one-liner. ([Google AI for Developers][1], [Google Developers Blog][2])
xAI Grok Integration
Added first-class support for Grok through the endpoint https://api.x.ai/v1/chat/completions. The default model is grok-3-latest. You also get get_grok_models() plus a "grok" flag in list_models() for painless switching. ([xAI Docs][3], [docs.typingmind.com][4])
Model Catalog Expansion
list_models("all") now aggregates catalogs from eight providers—OpenAI, Groq, Anthropic, DeepSeek, DashScope, GitHub, Gemini, and Grok—so you can inspect every available model in a single call.
DeepSeek Integration
chat_llm() now supports DeepSeek as a backend provider. This expands the range of available language models and increases flexibility for users selecting different inference engines.
Alibaba DashScope Integration
You can now use models from Alibaba Cloud’s Model Studio (DashScope) via OpenAI-compatible endpoints. This allows users in mainland China and beyond to easily integrate powerful Qwen-series models (like qwen-plus, qwen-turbo, and others) using the same chat_llm() interface.
GitHub Copilot-Compatible Model Integration
You can now use models hosted through GitHub Copilot-compatible endpoints. This allows seamless integration with custom-hosted or proxy-accessible models, making it easier to experiment with private or specialized deployments.
Model Catalog Access
chat_llm() now supports listing all available models across all supported providers. This makes it easier to discover and compare model options before selecting one for your workflow.