Chat$tokens() now returns a data frame of tokens, correctly aligned to the
individual turn. The print method now uses this to show how many input/output
tokens each turn used (#354).
All requests now set a custom User-Agent that identifies that the requests comes from ellmer (#341).
provider_claude() now supports content_image_url() (#347).
chat_claude() gains beta_header argument to opt-in to beta features (#339).
chat_claude() now supports content_image_url() (#347).
chat_claude() now defaults to Sonnet 3.7 and displays the default
model (#336).
Turn objects now include a POSIXct timestamp in the completed slot that
records when the turn was completed (#337, @simonpcouch).
create_tool_def() can now use any Chat instance (#118, @pedrobtz).
New experimental $chat_parallel() and $extract_data_parallel() make it
easier to perform multiple actions in parallel (#143). This is experimental
because I'm not 100% sure that the shape of the user interface is correct,
particularly as it pertains to handling errors.
For Claude, note that the number of active connections is limited primarily
by the output tokens per limit (OTPM) which is estimated from the max_tokens
parameter, which defaults to 4096. That means if you're limited to 16,000
OPTM, you should use at most 16,000 / 4096 = ~4 active connections (or
decrease max_tokens).
Parallel calls with OpenAI and Gemini are much simpler in my experience.
gemini_upload() lets you upload files to Gemini (#310).
chat_gemini() can now authenticate with Google default application
credentials (including service accounts, etc). This requires the gargle
package (#317, @atheriel).
chat_gemini() now detects viewer-based credentials when running on Posit
Connect (#320, @atheriel).
chat_ollama() now works with tool() definitions with optional arguments or empty properties (#342, #348, @gadenbuie).
option(ellmer_verbosity) is no longer supported; instead use the standard
httr2 verbosity functions, such as httr2::with_verbosity(); these now
support streaming data.
chat_cortex() has been renamed chat_cortex_analyst() to better
disambiguate it from chat_snowflake() (which also uses "Cortex")
(#275, @atheriel).
All providers now wait for up to 60s to get the complete response. You can
increase this with, e.g., option(ellmer_timeout_s = 120) (#213, #300).
chat_azure(), chat_databricks(), chat_snowflake(), and
chat_cortex_analyst() now detect viewer-based credentials when running on
Posit Connect (#285, @atheriel).
chat_deepseek() provides support for DeepSeek models (#242).
chat_openrouter() provides support for models hosted by OpenRouter (#212).
chat_snowflake() allows chatting with models hosted through Snowflake's
Cortex LLM REST API
(#258, @atheriel).
content_pdf_file() and content_pdf_url() allow you to upload PDFs to
supported models. Models that currently support PDFs are Google Gemini and
Claude Anthropic. With help from @walkerke and @andrie (#265).
Chat$get_model() returns the model name (#299).
chat_azure() has greatly improved support for Azure Entra ID. API keys are
now optional and we can pick up on ambient credentials from Azure service
principals or attempt to use interactive Entra ID authentication when
possible. The broken-by-design token argument has been deprecated (it
could not handle refreshing tokens properly), but a new credentials
argument can be used for custom Entra ID support when needed instead
(for instance, if you're trying to use tokens generated by the AzureAuth
package) (#248, #263, #273, #257, @atheriel).
chat_azure() now reports better error messages when the underlying HTTP
requests fail (#269, @atheriel). It now also defaults to
api_version = "2024-10-21" which includes data for structured data
extraction (#271).
chat_bedrock() now handles temporary IAM credentials better
(#261, @atheriel) and chat_bedrock() gains api_args argument (@billsanto, #295).
chat_databricks() now handles the DATABRICKS_HOST environment variable
correctly whether it includes an HTTPS prefix or not (#252, @atheriel).
It also respects the SPARK_CONNECT_USER_AGENT environment variable when
making requests (#254, @atheriel).
chat_gemini() now defaults to using the gemini-2.0-flash model.
print(Chat) no longer wraps long lines, making it easier to read code
and bulleted lists (#246).
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).