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Changelog

Source: NEWS.md

chatLLM 0.1.4 (Upcoming Release - February 2026)

New Features

  • 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.

Improvements

  • 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.

chatLLM 0.1.3 (Upcoming Release - August 2025)

CRAN release: 2025-08-19

New Features

  • 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, Google Developers Blog)

  • 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, docs.typingmind.com)

  • 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.

chatLLM 0.1.2 (Upcoming Release – May 2025)

CRAN release: 2025-05-20

New Features

  • 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.