Added #

• LLMFinishReason.resolve and LLMFinishReason.canBecomeToolCalls — the shared rule for classifying a tool-call turn, so every backend applies it identically instead of each re-deriving it.

Fixed #

• chatResponse returned toolCalls: null for Ollama, Claude and Gemini. It captured calls only from chunks with done: true, and all three deliver complete calls on an earlier chunk. Calls are now attributed to the turn that carried them, and calls the tool loop already executed are still excluded.
• LLMResponse.finishReason could contradict LLMResponse.toolCalls. The finish reason is now resolved against the calls actually returned, so a backend that does not classify the turn itself still yields a consistent response.

Changed #

• A turn that ends while carrying complete tool calls now reports LLMFinishReason.toolCalls, whatever the provider spelled. The OpenAI specification defines finish_reason as tool_calls "if the model called a tool", and providers violate it routinely. Code branching on LLMFinishReason.stop for a tool-calling turn must move to toolCalls. length, contentFilter and refusal are never reclassified: a truncated call is not executable, and a declined turn must stay visibly declined.

Added #

• LLMToolCallDelta and LLMChunkMessage.toolCallDeltas — fragments of a tool call that is still streaming. Backends announce the tool's name in their first event, so a caller can show which tool is running without waiting for its arguments.

Fixed #

• Tool calls that take no arguments always failed. A zero-parameter tool is routinely called with "" (OpenAI-compatible servers) or with nothing to concatenate (Anthropic), and decoding that as JSON threw — the executor answered Tool x failed: FormatException and the message converters that replay history threw outright. LLMToolCall.argumentsJson now reads no arguments as an empty map; genuinely malformed JSON still throws.
• Token counts survive a turn that ends in more than one done chunk. Several backends report the finish reason first and token usage in a trailing frame, and a tool loop produces a done chunk per round; counts were assigned unconditionally, so a later count-less chunk erased them.
• 529 is retryable by default. It is Anthropic's transient "overloaded" signal, and its absence meant those failures were never retried.
• ToolLoopIncompleteException.attemptsUsed reported 0 no matter how many tool rounds had run. Each recursion builds a fresh executor whose budget is already decremented, so the frame that runs out cannot see the rounds behind it; the accounting is now restated as the error unwinds, and the outermost frame — which knows the real ceiling — supplies the final number.

Changed #

• LLMChunkMessage.toolCalls is documented as only ever holding complete, executable calls. Deltas are never executable and never appear there.

Changed #

• Version bumped to 0.3.2 in lockstep with the other packages. No changes to this package.

Added #

• createLLMHttpClient() — the default HTTP client for every backend. Applies TimeoutConfig.connectionTimeout, bounds the pool per host, and retires idle connections after 3s.
• WriteGatedHttpClient — bounds how many requests may be connecting and writing at once (4 slots on macOS/iOS) to work around a Dart VM kqueue defect that loses writable events. See docs/concurrent-send-stall.md.
• LLMChunkMessage.rawContent — the assistant turn as the model emitted it, tool-call markup intact. Set by local-inference backends.
• RetryUtil.executeWithRetry accepts an onRetry callback and warns on every retry.

Changed #

• HttpClientHelper.sendStreamingRequest now applies a timeout to send() by default. It previously did not, so a request that wedged before response headers arrived never recovered.
• Streaming requests are built with http.Request + bodyBytes instead of StreamedRequest.
• Dependency floors raised: Dart SDK ^3.12.0 (was ^3.8.0), http ^1.6.0, lints ^6.1.0, test ^1.31.0.

Added #

• ReasoningEffort enum (none…max) and LLMChatOptions.reasoningEffort — a portable reasoning-depth knob alongside reasoningBudget.
• reasoningEffortForBudget() for backends without a native token budget.
• LLMUsage.reasoningTokens for providers that report reasoning-token usage.

Fixed #

• LLMFinishReason.fromProvider now recognizes stop_sequence, model_context_window_exceeded, refusal, and Gemini's RECITATION / PROHIBITED_CONTENT / BLOCKLIST / SPII / IMAGE_SAFETY, which previously all collapsed to unknown.

Added #

• LLMFinishReason.refusal for provider safety declines, which arrive as successful responses with empty or partial content.
• Typed message content parts, typed tool calls, provider capabilities, response usage, finish reasons, thinking output, and provider metadata.
• LLMChatOptions for generation, reasoning, tool behavior, structured output, timeout, retry, cache, metrics, and backend-specific options.
• Shared repository feature helpers for cache and metrics handling.
• LLMResponseFormat sealed class hierarchy for structured output:
  • JsonFormat — simple JSON mode; instructs the model to produce valid JSON without schema enforcement
  • JsonSchemaFormat({required name, required schema, strict = true}) — full JSON Schema mode; schema is forwarded to the backend verbatim
  • Both are const-constructible and work with exhaustive switch pattern matching
• responseFormat field on StreamChatOptions (nullable, defaults to null; fully backward compatible)
• StreamChatOptionsMerger and MergedOptions now carry and propagate responseFormat

Changed #

• Breaking: Core chat APIs now accept LLMChatOptions?; StreamChatOptions remains as a compatibility alias.
• Cache keys now use stable JSON-shaped request data instead of object stringification.

Changed #

• Breaking: Removed requireFinalAssistantResponse option from StreamChatOptions, StreamChatOptionsMerger, and StreamToolExecutor. Tool loops now always require a final assistant response — there is no reason to allow tool loops to end without the assistant reporting back.
• maxToolAttempts default increased from 25 to 90 across all repositories and builders.
• chatResponse() tool loop detection refined: only actual tool result chunks (LLMRole.tool) trigger the incomplete-loop check, not tool calls appearing alongside content.

Added #

• Tool result chunks emitted to stream: StreamToolExecutor now yields LLMChunk with role: LLMRole.tool after each tool execution, so chat consumers can display "Tool X returned: Y" per OpenAI function calling specs
• LLMToolCall.toApiFormat() helper for converting to OpenAI/Ollama API format
• Assistant message with tool_calls added to message history before tool results (API-compliant sequence)
• Content accumulation from stream chunks for assistant messages that include both text and tool calls

Changed #

• Breaking: Removed toolName from LLMMessage and LLMChunkMessage; use toolCallId only (OpenAI canonical format)
• Breaking: Tool message validation now requires toolCallId (removed toolName option)
• StreamToolExecutor accumulates content and thinking from chunks for the assistant message

Added #

• batchEmbed() on LLMChatRepository: explicit API for embedding multiple texts in one call. Same signature as embed(); default implementation delegates to embed(). Documented for Ollama, OpenAI, and llama.cpp backends.

Fixed #

• Hardened StreamToolExecutor to always synthesize a non-empty toolCallId for LLMRole.tool messages when a backend-provided LLMToolCall.id is missing or empty, preventing Tool message must have toolCallId validation errors.
• Improved tool execution error handling so that thrown tool exceptions are surfaced as tool messages rather than crashing the stream.

Added #

• StreamChatOptions class to encapsulate all streaming chat options and reduce parameter proliferation
• RetryConfig and RetryUtil for configurable retry logic with exponential backoff
• TimeoutConfig for flexible timeout configuration (connection, read, total, large payloads)
• LLMMetrics interface and DefaultLLMMetrics implementation for optional metrics collection
• chatResponse() method on LLMChatRepository for non-streaming complete responses
• Input validation utilities in Validation class
• ChatRepositoryBuilderBase for implementing builder patterns in repository implementations
• StreamChatOptionsMerger for merging options from multiple sources
• HTTP client utilities (HttpClientHelper) for consistent request handling
• Error handling utilities (ErrorHandlers, BackendErrorHandler) for standardized error processing
• Tool execution utilities (ToolExecutor) for managing tool calling workflows

Changed #

• streamChat() now accepts optional StreamChatOptions parameter
• Improved error handling and retry logic across all backends
• Enhanced documentation

Added #

• Initial release
• Core abstractions for LLM interactions:
  • LLMChatRepository - Abstract interface for chat completions
  • LLMMessage - Message representation with roles and content
  • LLMResponse - Response wrapper with metadata
  • LLMChunk - Streaming response chunks
  • LLMEmbedding - Text embedding representation
• Tool calling support:
  • LLMTool - Tool definition with JSON Schema parameters
  • LLMToolCall - Tool invocation representation
  • LLMToolParam - Parameter definitions
• Exception types for error handling