dartantic_ai 0.9.6

A Dart library for easily interacting with LLMs in a typed manner.

0.9.6

• fixed an issue where the OpenAI model only processed the last tool result when multiple tool results existed in a single message, causing unmatched tool call IDs during provider switching.

0.9.5

• Major OpenAI Multi-Step Tool Calling Improvement: Eliminated complex probe mechanism (100+ lines of code) in favor of OpenAI's native parallelToolCalls parameter. This dramatically simplifies the implementation while improving reliability and performance.

0.9.4

• README & docs tweaks

0.9.3

• Completely revamped docs! https://docs.page/csells/dartantic_ai

0.9.2

• Added Agent.environment to allow setting environment variables programmatically. This is especially useful for web applications where traditional environment variables are not available.

0.9.1

• Added support for extending the provider table at runtime, allowing custom providers to be registered dynamically.

• Added optional name parameter to DataPart and LinkPart for better multi-media message creation ergonomics.

0.9.0

• Added ToolCallingMode to control multi-step tool calling behavior.

  • multiStep (default): The agent will continue to send tool results until all of the tool calls have been exercised.
  • singleStep: The agent will perform only one request-response and then stop.

• OpenAI Multi-Step Tool Calling by including probing for additional tool calls when the model responds with text instead of a tool call.

• Gemini multi-step tool calling by handling new tool calls while processing the response from previous tool calling.

• Schema Nullable Properties Fix: Required properties in JSON schemas now correctly set nullable: false in converted Gemini schemas, since required properties cannot be null by definition.

0.8.3

• Breaking Change: McpServer → McpClient: Renamed MCP integration class cuz we're not building a server!
• MCP Required Fields Preservation: Enhanced MCP integration to preserve required fields in tool schemas, allowing LLMs to know what parameters are required for each tool call. This turns out to be a critical piece in whether the LLM is able to call the tool correctly or not.
• Model discovery: Added Provider.listModels() to enumerate available models, and the kinds of operations they support and whether they're in stable or preview/experimental mode.
• Breaking Change: simplifying provider names (again!)
• no change to actual provider aliases, e.g. "gemini" still maps to "google"
• fixed a nasty fully-qualified model naming bug
• Better docs!

0.8.2

• Better docs!

0.8.1

• Breaking change: Content=>List

0.8.0

• Multimedia Input Support: Added attachments parameter to Agent and Model interfaces for including files, data and links.
• Improved OpenAI compatibility for tool calls
• Added the 'gemini-compat' provider for access to Gemini models via the OpenAI endpoint.
• Breaking change: everywhere I passed List

0.7.0

• Provider Capabilities System: Add support for providers to declare their capabilities
• baseUrl support to enable OpenAI-compatibility
• Added new "openrouter" provider
  • it's an OpenAI API implementation, but doesn't support embeddings
  • which drove support for provider capabilities...
• temperature support
• Breaking change: McpServer.remote now takes a Uri instead of a String for the URL
• Breaking change: Renamed model interface properties for clarity:
  • Model.modelName → Model.generativeModelName
  • Also added Model.embeddingModelName
• Breaking change: Provider capabilities API naming:
  • Provider.caps returns Set<ProviderCaps> instead of Iterable<ProviderCaps>

0.6.0

• MCP (Model Context Protocol) Server Support
• Message construction convenience methods:
  • Added Content type alias for List<Part> to improve readability
  • Added convenience constructors for Message: Message.system(), Message.user(), Message.model()
  • Added Content.text() extension method for easy text content creation
  • Added convenience constructors for ToolPart: ToolPart.call() and ToolPart.result()
• Breaking change: inputType/outputType to inputSchema/outputSchema; I couldn't stand to look at inputType and outputType in the code anymore!
• Add logging support (defaults to off) and a logging example

0.5.0

• Embedding generation: Add methods to generate vector embeddings for text

0.4.0

• Streaming responses via Agent.runStream and related methods.
• Multi-turn chat support
• Provider switching: seamlessly alternate between multiple providers in a single conversation, with full context and tool call/result compatibility.

0.3.0

• added dotprompt_dart package support via Agent.runPrompt(DotPrompt prompt)
• expanded model naming to include "providerName", "providerName:model" or "providerName/model", e.g. "openai" or "googleai/gemini-2.0-flash"
• move types specified by Map<String, dynamic> to a JsonSchema object; added toMap() extension method to JsonSchema and toSchema to Map<String, dynamic> to make going back and forth more convenient.
• move the provider argument to Agent.provider as the most flexible case, but also the less common one. Agent() will contine to take a model string.

0.2.0

• Define tools and their inputs/outputs easily
• Automatically generate LLM-specific tool/output schemas
• Allow for a model descriptor string that just contains a family name so that the provider can choose the default model.

0.1.0

• Multi-Model Support (just Gemini and OpenAI models so far)
• Create agents from model strings (e.g. openai:gpt-4o) or typed providers (e.g. GoogleProvider())
• Automatically check environment for API key if none is provided (not web compatible)
• String output via Agent.run
• Typed output via Agent.runFor

0.0.1

• Initial version.