New chat_vllm() to chat with models served by vLLM
(#140).
The default chat_openai() model is now
GPT-4o.
New Chat$set_turns() to set turns.
Chat$turns() is now Chat$get_turns().
Chat$system_prompt() is replaced with
Chat$set_system_prompt() and
Chat$get_system_prompt().
Async and streaming async chat are now event-driven and use
later::later_fd() to wait efficiently on curl socket
activity (#157).
New chat_bedrock() to chat with AWS bedrock models
(#50).
New chat$extract_data() uses the structured data API
where available (and tool calling otherwise) to extract data structured
according to a known type specification. You can create specs with
functions type_boolean(), type_integer(),
type_number(), type_string(),
type_enum(), type_array(), and
type_object() (#31).
The general ToolArg() has been replaced by the more
specific type_*() functions. ToolDef() has
been renamed to tool.
content_image_url() will now create inline images
when given a data url (#110).
Streaming ollama results works once again (#117).
Streaming OpenAI results now capture more results, including
logprops (#115).
New interpolate() and prompt_file()
make it easier to create prompts that are a mix of static text and
dynamic values.
You can find how many tokens you’ve used in the current session
by calling token_usage().
chat_browser() and chat_console() are
now live_browser() and
live_console().
The echo can now be one of three values: “none”,
“text”, or “all”. If “all”, you’ll now see both user and assistant
turns, and all content types will be printed, not just text. When
running in the global environment, echo defaults to “text”,
and when running inside a function it defaults to “none”.
You can now log low-level JSON request/response info by setting
options(ellmer_verbosity = 2).
chat$register_tool() now takes an object created by
Tool(). This makes it a little easier to reuse tool
definitions (#32).
new_chat_openai() is now
chat_openai().
Claude and Gemini are now supported via
chat_claude() and chat_gemini().
The Snowflake Cortex Analyst is now supported via
chat_cortex() (#56).
Databricks is now supported via chat_databricks()
(#152).