0.2 — 2026-04-14

Core SDK (ai_core)

• Smooth_stream — stream transformer that buffers Text_delta and Reasoning_delta chunks and re-emits them in controlled pieces with configurable inter-chunk delays. Five chunking modes: Word (default), Line, Regex (custom Re2 pattern), Segmenter (Unicode UAX#29 word boundaries via uuseg, recommended for CJK), and Custom (user function). Matches the upstream AI SDK's smoothStream transform.
• ?transform parameter on stream_text and server_handler.handle_chat — generic stream transformer (Text_stream_part.t Lwt_stream.t -> Text_stream_part.t Lwt_stream.t) applied between the raw event stream and consumer-facing streams. Both full_stream and text_stream reflect the transformed output.
• Retry with exponential backoff — Retry module with jitter, configurable initial delay and backoff factor, and parameter validation. ?max_retries threaded through generate_text, stream_text, and server_handler.handle_chat. Retries only on errors marked retryable.
• Telemetry / observability — Telemetry module with OpenTelemetry-compatible span instrumentation via the trace library (ocaml-trace). Configurable Telemetry.t settings control enable/disable, input/output recording privacy, function ID, custom metadata, and lifecycle integration callbacks (on_start, on_step_finish, on_tool_call_start, on_tool_call_finish, on_finish). Span hierarchy matches upstream AI SDK: ai.generateText / ai.streamText root spans, *.doGenerate / *.doStream step spans, and ai.toolCall tool execution spans. ?telemetry parameter threaded through generate_text, stream_text, and server_handler.handle_chat.

Provider Abstraction Layer (ai_provider)

• is_retryable field on Provider_error.t — defaults from HTTP status code (429, 5xx are retryable). Anthropic and OpenAI providers set it explicitly based on error classification.

Examples

• smooth_streaming — demonstrates all five chunking modes
• telemetry_logging — demonstrates integration callbacks for lifecycle logging

Dependencies

• Added re2 (>= 0.16) and uuseg (>= 17.0) to ai_core
• Added trace (>= 0.12) to ai_core

0.1 — 2026-04-06

Initial release of the OCaml AI SDK — a type-safe, provider-agnostic AI model abstraction inspired by the Vercel AI SDK, targeting AI SDK v6 wire compatibility.

Provider Abstraction Layer (ai_provider)

• Extensible GADT-based Provider_options for compile-time type-safe provider-specific settings
• Role-constrained Prompt types (System = string only, User = text + files, etc.)
• Language_model.S module type with first-class module wrapper
• Tool, Tool_choice, Mode, Content foundation types
• Finish_reason, Usage, Warning, Provider_error types
• Provider.S and Middleware.S module type signatures
• Call_options, Generate_result, Stream_part, Stream_result types

Anthropic Provider (ai_provider_anthropic)

• Full Anthropic Messages API implementation with streaming (SSE)
• Thinking support with budget_tokens smart constructor (>= 1024)
• Cache_control for prompt caching
• Anthropic_options via the extensible GADT system
• Model catalog with all Claude models (Opus, Sonnet, Haiku families)
• Beta header management and model-aware max_tokens
• Prompt conversion with message grouping, tool conversion, response parsing
• Provider factory and public API

OpenAI Provider (ai_provider_openai)

• OpenAI Chat Completions API implementation with streaming (SSE)
• Model catalog with GPT-4o, GPT-4o-mini, o1, o3, o4-mini families
• Tool calling with strict mode support
• Prompt conversion, response parsing, and provider factory

Core SDK (ai_core)

• generate_text — synchronous text generation with multi-step tool loop
• stream_text — streaming text generation with multi-step tool loop, returns synchronously with streams filled by background Lwt task
• Output API — Output.text, Output.object_, Output.enum, Output.array, Output.choice with JSON Schema validation
• UIMessage stream protocol — SSE data: {json}\n\n encoding with x-vercel-ai-ui-message-stream: v1 header, all v6 chunk types
• Ui_message_stream_writer — composable stream builder with write (synchronous) and merge (non-blocking via Lwt.async), lifecycle management, ref-counted in-flight merge tracking, on_finish callback
• Server handler — cohttp endpoint for chat with CORS support, v6-only request parsing with full part type support (text, file, reasoning, tool invocations with all states)
• Tool approval workflow — needs_approval predicate on Core_tool.t, step loop partitioning, Tool_approval_request chunk type, stateless re-submission with approved_tool_call_ids
• Stop_condition — step loop termination predicates matching upstream stopWhen: step_count_is, has_tool_call, is_met (OR semantics with short-circuit); wired through generate_text, stream_text, and server_handler; max_steps remains as independent hard safety cap
• Partial JSON parser — for streaming structured output

Melange Bindings (ai-sdk-react)

• useChat and useCompletion hook bindings for @ai-sdk/react
• All v6 message part types including data_ui_part
• classify function for part type dispatch
• Module-scoped accessors for ergonomic use from OCaml/Reason

Examples

• one_shot, streaming, tool_use, thinking, generate, stream_chat, agent_loop — standalone CLI examples
• chat_server — cohttp chat server with React frontend, tool approval, structured output
• custom_stream — custom data streaming with Melange frontend
• ai-e2e — end-to-end Melange app with 11 demos (basic chat, reasoning, tool use, tool approval, client tools, file attachments, structured output, completion, web search, retry/regenerate)

Infrastructure

• Dune build with generate_opam_files for automated opam file generation
• mlx dialect support (OCaml + JSX via mlx-pp / ocamlformat-mlx)
• Alcotest test suites for all three libraries
• SSE wire format snapshot tests