From 7b1a50e0d85e03943e1a4982b82e0c519ee2246b Mon Sep 17 00:00:00 2001 From: svilupp Date: Fri, 28 Nov 2025 07:13:50 -0600 Subject: [PATCH 1/4] add reasoning --- CHANGELOG.md | 10 + CLAUDE.md | 76 +++ Makefile | 14 + Project.toml | 6 +- README.md | 49 +- docs/src/index.md | 45 +- ...enai_example.jl => openai_chat_example.jl} | 6 +- examples/openai_responses_example.jl | 24 + scripts/bootstrap_with_llm.jl | 2 +- src/StreamCallbacks.jl | 8 +- src/interface.jl | 6 +- ...stream_openai.jl => stream_openai_chat.jl} | 26 +- src/stream_openai_responses.jl | 171 ++++++ test/fixtures/chat_completions_simple.txt | 24 + test/fixtures/responses_api_reasoning.txt | 561 ++++++++++++++++++ test/fixtures/responses_api_simple.txt | 48 ++ test/integration_mock_server.jl | 359 +++++++++++ test/runtests.jl | 10 +- ...stream_openai.jl => stream_openai_chat.jl} | 0 test/stream_openai_responses.jl | 531 +++++++++++++++++ 20 files changed, 1925 insertions(+), 51 deletions(-) create mode 100644 CLAUDE.md create mode 100644 Makefile rename examples/{openai_example.jl => openai_chat_example.jl} (82%) create mode 100644 examples/openai_responses_example.jl rename src/{stream_openai.jl => stream_openai_chat.jl} (81%) create mode 100644 src/stream_openai_responses.jl create mode 100644 test/fixtures/chat_completions_simple.txt create mode 100644 test/fixtures/responses_api_reasoning.txt create mode 100644 test/fixtures/responses_api_simple.txt create mode 100644 test/integration_mock_server.jl rename test/{stream_openai.jl => stream_openai_chat.jl} (100%) create mode 100644 test/stream_openai_responses.jl diff --git a/CHANGELOG.md b/CHANGELOG.md index bd4dc63..1740c1e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -10,6 +10,16 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ### Fixed +## [0.7.0] + +### Added +- Added `OpenAIResponsesStream` flavor for OpenAI Responses API (`/v1/responses`) +- Added `OpenAIChatStream` as the preferred name for Chat Completions API (with `OpenAIStream` as alias) +- Added integration tests with fixture-based SSE server +- Added `examples/openai_responses_example.jl` for Responses API usage +- Renamed `examples/openai_example.jl` to `examples/openai_chat_example.jl` +- Updated documentation to cover both OpenAI API flavors + ## [0.6.2] ### Fixed diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 0000000..84494e7 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,76 @@ +# CLAUDE.md + +This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository. + +## Project Overview + +StreamCallbacks.jl is a Julia package that provides a unified streaming interface for Large Language Model (LLM) APIs. It handles Server-Sent Events (SSE) parsing, chunk processing, and response body reconstruction across multiple providers. + +## Common Commands + +```bash +# Run all tests +julia --project -e 'using Pkg; Pkg.test()' + +# Run a single test file +julia --project -e 'using StreamCallbacks; include("test/stream_openai_chat.jl")' + +# Start Julia REPL with project +julia --project + +# Build documentation locally +julia --project=docs docs/make.jl +``` + +## Architecture + +### Core Types (`src/interface.jl`) + +- `AbstractStreamFlavor` - Base type for provider-specific streaming behavior + - `OpenAIStream` / `OpenAIChatStream` - OpenAI Chat Completions API + - `OpenAIResponsesStream` - OpenAI Responses API + - `AnthropicStream`, `OllamaStream` - Anthropic and Ollama APIs +- `StreamChunk` - Represents a single SSE chunk with `event`, `data`, and parsed `json` +- `StreamCallback` - Main callback object that accumulates chunks and manages output + +### Provider-Specific Files + +Each provider has its own file implementing three key methods: +- `is_done(flavor, chunk)` - Detect stream termination +- `extract_content(flavor, chunk)` - Extract displayable text from chunk +- `build_response_body(flavor, cb)` - Reconstruct standard API response from chunks + +| File | Provider | Flavor | Termination Signal | +|------|----------|--------|-------------------| +| `src/stream_openai_chat.jl` | OpenAI Chat Completions | `OpenAIStream` | `[DONE]` data | +| `src/stream_openai_responses.jl` | OpenAI Responses API | `OpenAIResponsesStream` | `response.completed` event | +| `src/stream_anthropic.jl` | Anthropic | `AnthropicStream` | `:message_stop` event | +| `src/stream_ollama.jl` | Ollama | `OllamaStream` | `done: true` in JSON | + +### Request Flow + +1. `streamed_request!(cb, url, headers, input)` - Entry point in `src/shared_methods.jl` +2. `extract_chunks(flavor, blob)` - Parse SSE blob into `StreamChunk` array (handles spillover for incomplete messages) +3. For each chunk: `callback(cb, chunk)` → `extract_content()` → `print_content()` +4. `build_response_body(flavor, cb)` - Reconstruct response mimicking non-streaming API + +### Extending the Package + +To add a new provider: +1. Create new `AbstractStreamFlavor` subtype +2. Implement `is_done`, `extract_content`, and `build_response_body` methods +3. Export the new flavor type + +To customize output handling: +- Extend `print_content(out, text)` for custom sinks (IO, Channel, or custom types) +- Create custom callback by subtyping `AbstractStreamCallback` + +## Dependencies + +- HTTP.jl - HTTP requests and SSE streaming +- JSON3.jl - JSON parsing +- PrecompileTools.jl - Precompilation workloads + +## Integration + +This package integrates with PromptingTools.jl via `configure_callback!` which auto-configures the `StreamCallback` flavor and necessary `api_kwargs`. diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..ebe49d4 --- /dev/null +++ b/Makefile @@ -0,0 +1,14 @@ +# This is not a true makefile, just a collection of convenient scripts + +default: help + +format: + # assumes you have JuliaFormatter installed in your global env / somewhere on LOAD_PATH + julia --project=@Fmt -e 'using JuliaFormatter; format(".")' + +test: + julia --project=. -e 'using Pkg; Pkg.test()' + +help: + echo "make help - show this help" + echo "make format - format the code" \ No newline at end of file diff --git a/Project.toml b/Project.toml index dbd9cd9..2e5d646 100644 --- a/Project.toml +++ b/Project.toml @@ -1,7 +1,7 @@ name = "StreamCallbacks" uuid = "c1b9e933-98a0-46fc-8ea7-3b58b195fb0a" authors = ["J S <49557684+svilupp@users.noreply.github.com> and contributors"] -version = "0.6.2" +version = "0.7.0" [deps] HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3" @@ -13,12 +13,14 @@ Aqua = "0.8" HTTP = "1.10" JSON3 = "1.14" PrecompileTools = "1.2" +Sockets = "1" Test = "1" julia = "1.9" [extras] Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595" +Sockets = "6462fe0b-24de-5631-8697-dd941f90decc" Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" [targets] -test = ["Aqua", "Test"] +test = ["Aqua", "Sockets", "Test"] diff --git a/README.md b/README.md index 4ad03f5..3baca76 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,8 @@ StreamCallbacks.jl is designed to unify streaming interfaces for Large Language - [Installation](#installation) - [Getting Started](#getting-started) - [Usage Examples](#usage-examples) - - [Example with OpenAI API](#example-with-openai-api) + - [OpenAI Chat Completions API](#openai-chat-completions-api) + - [OpenAI Responses API](#openai-responses-api) - [Example with PromptingTools.jl](#example-with-promptingtoolsjl) - [Extending StreamCallbacks.jl](#extending-streamcallbacksjl) - [StreamCallback Interface](#streamcallback-interface) @@ -28,8 +29,12 @@ StreamCallbacks.jl is designed to unify streaming interfaces for Large Language ## Supported Providers - **OpenAI API** (and all compatible providers) -- **Anthropic API** -- **Ollama API** (`api/chat` endpoint, OpenAI-compatible endpoint) + - `OpenAIChatStream` (alias: `OpenAIStream`) for Chat Completions API (`/v1/chat/completions`) + - `OpenAIResponsesStream` for Responses API (`/v1/responses`) +- **Anthropic API** (`AnthropicStream`) +- **Ollama API** (`OllamaStream` for `/api/chat` endpoint) + +When used with PromptingTools.jl, these flavors map to `AbstractOpenAISchema` and `AbstractOpenAIResponsesSchema` respectively. ## Installation @@ -55,36 +60,44 @@ cb = StreamCallback(out = stdout) ## Usage Examples -### Example with OpenAI API +### OpenAI Chat Completions API ```julia -using HTTP -using JSON3 -using StreamCallbacks +using HTTP, JSON3, StreamCallbacks -# Prepare target URL and headers url = "https://api.openai.com/v1/chat/completions" headers = [ "Content-Type" => "application/json", - "Authorization" => "Bearer $(get(ENV, "OPENAI_API_KEY", ""))" + "Authorization" => "Bearer $(ENV["OPENAI_API_KEY"])" ] -# Create a StreamCallback object -cb = StreamCallback(out = stdout, flavor = OpenAIStream()) - -# Prepare the request payload -messages = [Dict("role" => "user", "content" => "Count from 1 to 100.")] +cb = StreamCallback(out = stdout, flavor = OpenAIChatStream()) +messages = [Dict("role" => "user", "content" => "What is 2+2?")] payload = IOBuffer() JSON3.write(payload, (; stream = true, messages, model = "gpt-4o-mini", stream_options = (; include_usage = true))) -# Send the streamed request resp = streamed_request!(cb, url, headers, payload) +``` + +### OpenAI Responses API + +```julia +using HTTP, JSON3, StreamCallbacks -# Check the response -println("Response status: ", resp.status) +url = "https://api.openai.com/v1/responses" +headers = [ + "Content-Type" => "application/json", + "Authorization" => "Bearer $(ENV["OPENAI_API_KEY"])" +] + +cb = StreamCallback(out = stdout, flavor = OpenAIResponsesStream()) +payload = IOBuffer() +JSON3.write(payload, (; stream = true, input = "What is 2+2?", model = "gpt-4o-mini")) + +resp = streamed_request!(cb, url, headers, payload) ``` -**Note**: For debugging, you can set `verbose = true` in the `StreamCallback` constructor to get detailed logs of each chunk. Ensure you enable DEBUG logging level in your environment. +**Note**: For debugging, set `verbose = true` in the `StreamCallback` constructor and enable DEBUG logging level. ### Example with PromptingTools.jl diff --git a/docs/src/index.md b/docs/src/index.md index c8d44d2..5376fce 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -16,7 +16,12 @@ StreamCallbacks.jl is designed to unify streaming interfaces for Large Language ## Supported Providers - **OpenAI API** (and all compatible providers) -- **Anthropic API** + - `OpenAIChatStream` (alias: `OpenAIStream`) for Chat Completions API (`/v1/chat/completions`) + - `OpenAIResponsesStream` for Responses API (`/v1/responses`) +- **Anthropic API** (`AnthropicStream`) +- **Ollama API** (`OllamaStream` for `/api/chat` endpoint) + +When used with PromptingTools.jl, these flavors map to `AbstractOpenAISchema` and `AbstractOpenAIResponsesSchema` respectively. ## Installation @@ -42,36 +47,44 @@ cb = StreamCallback(out = stdout) ## Usage Examples -### Example with OpenAI API +### OpenAI Chat Completions API ```julia -using HTTP -using JSON3 -using StreamCallbacks +using HTTP, JSON3, StreamCallbacks -# Prepare target URL and headers url = "https://api.openai.com/v1/chat/completions" headers = [ "Content-Type" => "application/json", - "Authorization" => "Bearer $(get(ENV, "OPENAI_API_KEY", ""))" + "Authorization" => "Bearer $(ENV["OPENAI_API_KEY"])" ] -# Create a StreamCallback object -cb = StreamCallback(out = stdout, flavor = OpenAIStream()) - -# Prepare the request payload -messages = [Dict("role" => "user", "content" => "Count from 1 to 100.")] +cb = StreamCallback(out = stdout, flavor = OpenAIChatStream()) +messages = [Dict("role" => "user", "content" => "What is 2+2?")] payload = IOBuffer() JSON3.write(payload, (; stream = true, messages, model = "gpt-4o-mini", stream_options = (; include_usage = true))) -# Send the streamed request resp = streamed_request!(cb, url, headers, payload) +``` + +### OpenAI Responses API + +```julia +using HTTP, JSON3, StreamCallbacks -# Check the response -println("Response status: ", resp.status) +url = "https://api.openai.com/v1/responses" +headers = [ + "Content-Type" => "application/json", + "Authorization" => "Bearer $(ENV["OPENAI_API_KEY"])" +] + +cb = StreamCallback(out = stdout, flavor = OpenAIResponsesStream()) +payload = IOBuffer() +JSON3.write(payload, (; stream = true, input = "What is 2+2?", model = "gpt-4o-mini")) + +resp = streamed_request!(cb, url, headers, payload) ``` -**Note**: For debugging, you can set `verbose = true` in the `StreamCallback` constructor to get detailed logs of each chunk. Ensure you enable DEBUG logging level in your environment. +**Note**: For debugging, set `verbose = true` in the `StreamCallback` constructor and enable DEBUG logging level. ### Example with PromptingTools.jl diff --git a/examples/openai_example.jl b/examples/openai_chat_example.jl similarity index 82% rename from examples/openai_example.jl rename to examples/openai_chat_example.jl index 7f233bb..c889f14 100644 --- a/examples/openai_example.jl +++ b/examples/openai_chat_example.jl @@ -1,4 +1,4 @@ -# Calling OpenAI with StreamCallbacks +# Calling OpenAI Chat Completions API with StreamCallbacks using HTTP, JSON3 using StreamCallbacks @@ -6,11 +6,11 @@ using StreamCallbacks url = "https://api.openai.com/v1/chat/completions" headers = [ "Content-Type" => "application/json", - "Authorization" => "Bearer $(get(ENV, "OPENAI_API_KEY", ""))" + "Authorization" => "Bearer $(ENV["OPENAI_API_KEY"])" ]; ## Send the request -cb = StreamCallback(; out = stdout, flavor = OpenAIStream()) +cb = StreamCallback(; out = stdout, flavor = OpenAIChatStream()) messages = [Dict("role" => "user", "content" => "Count from 1 to 100.")] payload = IOBuffer() diff --git a/examples/openai_responses_example.jl b/examples/openai_responses_example.jl new file mode 100644 index 0000000..1816259 --- /dev/null +++ b/examples/openai_responses_example.jl @@ -0,0 +1,24 @@ +# Calling OpenAI Responses API with StreamCallbacks +using HTTP, JSON3 +using StreamCallbacks + +## Prepare target and auth +url = "https://api.openai.com/v1/responses" +headers = [ + "Content-Type" => "application/json", + "Authorization" => "Bearer $(ENV["OPENAI_API_KEY"])" +]; + +## Send the request +cb = StreamCallback(; out = stdout, flavor = OpenAIResponsesStream()) +payload = IOBuffer() +JSON3.write(payload, (; stream = true, input = "Count from 1 to 20", model = "gpt-5-mini")) +resp = streamed_request!(cb, url, headers, payload); + +## Check the response +resp # should be a `HTTP.Response` object with a reconstructed response body + +## Check the callback +cb.chunks # should be a vector of `StreamChunk` objects with received SSE events + +# TIP: For debugging, use `cb.verbose = true` in the `StreamCallback` constructor and enable DEBUG loglevel. diff --git a/scripts/bootstrap_with_llm.jl b/scripts/bootstrap_with_llm.jl index ba68d5d..9c6ba36 100644 --- a/scripts/bootstrap_with_llm.jl +++ b/scripts/bootstrap_with_llm.jl @@ -92,7 +92,7 @@ purpose = "Library to unify streaming interfaces for LLMs across many providers. # # Update README task = """Update the provided README.md file with best in class information for what the package could be. Highlight that the package in experimental stage and under development (use strong warning at the top).""" -user_files = files_to_prompt(["README.md", "examples/openai_example.jl"]) +user_files = files_to_prompt(["README.md", "examples/openai_chat_example.jl"]) conv = aigenerate(tpl; pkg_name, purpose, user_files, task, model = "gpt4o", return_all = true) diff --git a/src/StreamCallbacks.jl b/src/StreamCallbacks.jl index 8230bb7..836bf3c 100644 --- a/src/StreamCallbacks.jl +++ b/src/StreamCallbacks.jl @@ -3,13 +3,15 @@ module StreamCallbacks using HTTP, JSON3 using PrecompileTools -export StreamCallback, StreamChunk, OpenAIStream, AnthropicStream, OllamaStream, - streamed_request! +export StreamCallback, StreamChunk, OpenAIStream, OpenAIChatStream, OpenAIResponsesStream, + AnthropicStream, OllamaStream, streamed_request! include("interface.jl") include("shared_methods.jl") -include("stream_openai.jl") +include("stream_openai_chat.jl") + +include("stream_openai_responses.jl") include("stream_anthropic.jl") diff --git a/src/interface.jl b/src/interface.jl index d150772..7e35355 100644 --- a/src/interface.jl +++ b/src/interface.jl @@ -64,11 +64,15 @@ abstract type AbstractStreamCallback end Abstract type for the stream flavor, ie, the API provider. Available flavors: -- `OpenAIStream` for OpenAI API +- `OpenAIStream` / `OpenAIChatStream` for OpenAI Chat Completions API +- `OpenAIResponsesStream` for OpenAI Responses API - `AnthropicStream` for Anthropic API +- `OllamaStream` for Ollama API """ abstract type AbstractStreamFlavor end struct OpenAIStream <: AbstractStreamFlavor end +const OpenAIChatStream = OpenAIStream +struct OpenAIResponsesStream <: AbstractStreamFlavor end struct AnthropicStream <: AbstractStreamFlavor end struct OllamaStream <: AbstractStreamFlavor end diff --git a/src/stream_openai.jl b/src/stream_openai_chat.jl similarity index 81% rename from src/stream_openai.jl rename to src/stream_openai_chat.jl index 679c47f..2ac8b51 100644 --- a/src/stream_openai.jl +++ b/src/stream_openai_chat.jl @@ -1,8 +1,27 @@ -# Custom methods for OpenAI streaming -- flavor=OpenAIStream() +# OpenAI Chat Completions API Streaming +# ====================================== +# +# This file implements streaming support for OpenAI's Chat Completions API +# (POST /v1/chat/completions with stream=true). +# +# Flavor: OpenAIStream (aliased as OpenAIChatStream) +# +# SSE Format: +# - Uses only `data:` field (no `event:` field) +# - Content located at: choices[].delta.content +# - Stream termination: `data: [DONE]` +# +# Example SSE message: +# data: {"id":"chatcmpl-xxx","choices":[{"delta":{"content":"Hello"}}]} +# +# Note: For the newer OpenAI Responses API (/v1/responses), see stream_openai_responses.jl +# which handles the richer event-based streaming format. + """ is_done(flavor::OpenAIStream, chunk::AbstractStreamChunk; kwargs...) -Check if the streaming is done. Shared by all streaming flavors currently. +Check if the streaming is done for OpenAI Chat Completions API. +Returns true when `data: [DONE]` is received. """ @inline function is_done(flavor::OpenAIStream, chunk::AbstractStreamChunk; kwargs...) chunk.data == "[DONE]" @@ -11,7 +30,8 @@ end """ extract_content(flavor::OpenAIStream, chunk::AbstractStreamChunk; kwargs...) -Extract the content from the chunk. +Extract the content from a Chat Completions streaming chunk. +Content is located at `choices[].delta.content`. """ @inline function extract_content( flavor::OpenAIStream, chunk::AbstractStreamChunk; kwargs...) diff --git a/src/stream_openai_responses.jl b/src/stream_openai_responses.jl new file mode 100644 index 0000000..29b34e7 --- /dev/null +++ b/src/stream_openai_responses.jl @@ -0,0 +1,171 @@ +# OpenAI Responses API Streaming +# =============================== +# +# This file implements streaming support for OpenAI's Responses API +# (POST /v1/responses with stream=true). +# +# Flavor: OpenAIResponsesStream +# +# SSE Format: +# - Uses both `event:` and `data:` fields +# - Event types include: response.created, response.output_text.delta, +# response.reasoning_summary_text.delta, response.completed, etc. +# - Content located at: delta field in delta events +# - Stream termination: response.completed, response.failed, or response.incomplete event +# +# Example SSE message: +# event: response.output_text.delta +# data: {"type":"response.output_text.delta","delta":"Hello","sequence_number":4} +# +# Key differences from Chat Completions API (stream_openai_chat.jl): +# - Richer event-based format with explicit event types +# - Supports reasoning summaries for reasoning models +# - No [DONE] signal - uses response.completed event instead +# - Hierarchical structure: response → output items → content parts + +""" + is_done(flavor::OpenAIResponsesStream, chunk::AbstractStreamChunk; kwargs...) + +Check if the Responses API stream is done. +Returns true when `response.completed`, `response.incomplete`, `response.failed`, or `error` event is received. +""" +@inline function is_done(flavor::OpenAIResponsesStream, chunk::AbstractStreamChunk; kwargs...) + chunk.event in ( + Symbol("response.completed"), + Symbol("response.incomplete"), + Symbol("response.failed"), + :error + ) +end + +""" + extract_content(flavor::OpenAIResponsesStream, chunk::AbstractStreamChunk; + include_reasoning::Bool = true, kwargs...) + +Extract content from Responses API chunks. +Handles both text deltas (`response.output_text.delta`) and reasoning deltas +(`response.reasoning_summary_text.delta`, `response.reasoning_text.delta`). + +# Arguments +- `include_reasoning::Bool = true`: Whether to include reasoning content in output. + Set to false to only extract final text output. +""" +@inline function extract_content( + flavor::OpenAIResponsesStream, chunk::AbstractStreamChunk; + include_reasoning::Bool = true, kwargs...) + isnothing(chunk.json) && return nothing + + # Handle text output deltas (main content) + if chunk.event == Symbol("response.output_text.delta") + return get(chunk.json, :delta, nothing) + end + + # Handle reasoning summary deltas (if enabled) + if include_reasoning && chunk.event == Symbol("response.reasoning_summary_text.delta") + return get(chunk.json, :delta, nothing) + end + + # Handle full reasoning text deltas (if enabled) + if include_reasoning && chunk.event == Symbol("response.reasoning_text.delta") + return get(chunk.json, :delta, nothing) + end + + return nothing +end + +""" + build_response_body(flavor::OpenAIResponsesStream, cb::AbstractStreamCallback; + verbose::Bool = false, kwargs...) + +Build response body from Responses API chunks to mimic a non-streaming response. +Reconstructs the final response structure with all output items, including +both text content and reasoning summaries. + +The response structure follows OpenAI's Responses API format with: +- `output`: Array of output items (reasoning and message) +- `usage`: Token usage statistics (from response.completed event) +""" +function build_response_body( + flavor::OpenAIResponsesStream, cb::AbstractStreamCallback; + verbose::Bool = false, kwargs...) + isempty(cb.chunks) && return nothing + + response = nothing + text_content = IOBuffer() + reasoning_content = IOBuffer() + usage = nothing + + for chunk in cb.chunks + isnothing(chunk.json) && continue + + # Capture response structure from response.completed (most complete) + if chunk.event == Symbol("response.completed") + resp_data = get(chunk.json, :response, nothing) + if !isnothing(resp_data) + response = copy(resp_data) + # Usage is nested in the response object + usage = get(resp_data, :usage, nothing) + end + end + + # Fallback: capture initial response structure from response.created + if isnothing(response) && chunk.event == Symbol("response.created") + resp_data = get(chunk.json, :response, nothing) + if !isnothing(resp_data) + response = copy(resp_data) + end + end + + # Accumulate text deltas + if chunk.event == Symbol("response.output_text.delta") + delta = get(chunk.json, :delta, nothing) + !isnothing(delta) && write(text_content, string(delta)) + end + + # Accumulate reasoning summary deltas + if chunk.event == Symbol("response.reasoning_summary_text.delta") + delta = get(chunk.json, :delta, nothing) + !isnothing(delta) && write(reasoning_content, string(delta)) + end + end + + # Build final response structure + if !isnothing(response) + final_text = String(take!(text_content)) + final_reasoning = String(take!(reasoning_content)) + + output = Dict{Symbol, Any}[] + + # Add reasoning output if present + if !isempty(final_reasoning) + push!(output, Dict{Symbol, Any}( + :type => "reasoning", + :summary => [Dict{Symbol, Any}(:type => "summary_text", :text => final_reasoning)] + )) + end + + # Add message output + if !isempty(final_text) + push!(output, Dict{Symbol, Any}( + :type => "message", + :role => "assistant", + :content => [Dict{Symbol, Any}(:type => "output_text", :text => final_text)] + )) + end + + # Only override output if we assembled content + # (response.completed already has the full output array) + if !isempty(output) && (isempty(final_text) == false || isempty(final_reasoning) == false) + # Check if response already has good output data from response.completed + existing_output = get(response, :output, []) + if isempty(existing_output) + response[:output] = output + end + end + + # Ensure usage is set + !isnothing(usage) && (response[:usage] = usage) + end + + return response +end diff --git a/test/fixtures/chat_completions_simple.txt b/test/fixtures/chat_completions_simple.txt new file mode 100644 index 0000000..8244b21 --- /dev/null +++ b/test/fixtures/chat_completions_simple.txt @@ -0,0 +1,24 @@ +data: {"id":"chatcmpl-Cgs6AeC1B2koF9Hzv0f3H3WysmOBD","object":"chat.completion.chunk","created":1764333766,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_50906f2aac","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"6eRnGpnsG"} + +data: {"id":"chatcmpl-Cgs6AeC1B2koF9Hzv0f3H3WysmOBD","object":"chat.completion.chunk","created":1764333766,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_50906f2aac","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"i9JTYkjGsl"} + +data: 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The key takeaway is simply that after giving away 1 apple, 2 remain."}]},{"id":"msg_0fb5070633854b5b00692990ffe59081918f3d732adbf2c331","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"You’ll have 2 apples left. 3 − 1 = 2."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"prompt_cache_retention":null,"reasoning":{"effort":"medium","summary":"detailed"},"safety_identifier":null,"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":28,"input_tokens_details":{"cached_tokens":0},"output_tokens":215,"output_tokens_details":{"reasoning_tokens":192},"total_tokens":243},"user":null,"metadata":{}}} + diff --git a/test/fixtures/responses_api_simple.txt b/test/fixtures/responses_api_simple.txt new file mode 100644 index 0000000..7118cb6 --- /dev/null +++ b/test/fixtures/responses_api_simple.txt @@ -0,0 +1,48 @@ +event: response.created +data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_01d1cd3b0fc9fafd00692990eb23a0819d881dc43acb22acff","object":"response","created_at":1764331755,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"prompt_cache_retention":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} + +event: response.in_progress +data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_01d1cd3b0fc9fafd00692990eb23a0819d881dc43acb22acff","object":"response","created_at":1764331755,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"prompt_cache_retention":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} + +event: response.output_item.added +data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","type":"message","status":"in_progress","content":[],"role":"assistant"}} + +event: response.content_part.added +data: {"type":"response.content_part.added","sequence_number":3,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":"2","logprobs":[],"obfuscation":"twDw7CMLMCWLc0J"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":" +","logprobs":[],"obfuscation":"6Y3ARQbQCZj2CO"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":6,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":" ","logprobs":[],"obfuscation":"3iQ7BEGHdqNTDU5"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":7,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":"2","logprobs":[],"obfuscation":"GulkazPvuupaYf7"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":8,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":" equals","logprobs":[],"obfuscation":"XTRWShv2J"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":9,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":" ","logprobs":[],"obfuscation":"ui72lRWpjM7ND7m"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":10,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":"4","logprobs":[],"obfuscation":"v9GQqlRenjwXUmI"} + +event: response.output_text.delta +data: {"type":"response.output_text.delta","sequence_number":11,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"delta":".","logprobs":[],"obfuscation":"NL09swDuyuNzUeF"} + +event: response.output_text.done +data: {"type":"response.output_text.done","sequence_number":12,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"text":"2 + 2 equals 4.","logprobs":[]} + +event: response.content_part.done +data: {"type":"response.content_part.done","sequence_number":13,"item_id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"2 + 2 equals 4."}} + +event: response.output_item.done +data: {"type":"response.output_item.done","sequence_number":14,"output_index":0,"item":{"id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"2 + 2 equals 4."}],"role":"assistant"}} + +event: response.completed +data: {"type":"response.completed","sequence_number":15,"response":{"id":"resp_01d1cd3b0fc9fafd00692990eb23a0819d881dc43acb22acff","object":"response","created_at":1764331755,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[{"id":"msg_01d1cd3b0fc9fafd00692990ecae1c819d9aad1c3c81358937","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"2 + 2 equals 4."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"prompt_cache_retention":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":14,"input_tokens_details":{"cached_tokens":0},"output_tokens":9,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":23},"user":null,"metadata":{}}} + diff --git a/test/integration_mock_server.jl b/test/integration_mock_server.jl new file mode 100644 index 0000000..ca9461b --- /dev/null +++ b/test/integration_mock_server.jl @@ -0,0 +1,359 @@ +# Integration tests with SSE server +# +# These tests spin up a local HTTP server that replays fixture files +# as SSE streams to verify end-to-end parsing and response reconstruction. + +using Sockets + +# Helper to find an available port +function find_available_port() + server = listen(0) + port = getsockname(server)[2] + close(server) + return port +end + +# Helper to read fixture file content +function read_fixture(filename) + filepath = joinpath(@__DIR__, "fixtures", filename) + return read(filepath, String) +end + +# Create an SSE server that streams fixture content +function create_sse_server(port, fixture_content; delay_ms = 0) + server = HTTP.listen!("127.0.0.1", port) do http + # Read and discard the request body to avoid EOF errors + try + read(http) + catch + end + + # Set SSE headers + HTTP.setstatus(http, 200) + HTTP.setheader(http, "Content-Type" => "text/event-stream") + HTTP.setheader(http, "Cache-Control" => "no-cache") + HTTP.setheader(http, "Connection" => "keep-alive") + HTTP.startwrite(http) + + # Stream the fixture content in chunks (split by double newlines) + messages = split(fixture_content, "\n\n") + for (i, message) in enumerate(messages) + if !isempty(strip(message)) + # Write the message with double newline separator + write(http, message * "\n\n") + + # Optional delay between messages to simulate real streaming + if delay_ms > 0 + sleep(delay_ms / 1000) + end + end + end + end + return server +end + +@testset "Integration-OpenAIResponsesStream" begin + # Test with simple responses fixture + @testset "simple-response" begin + port = find_available_port() + fixture_content = read_fixture("responses_api_simple.txt") + + server = create_sse_server(port, fixture_content) + + try + sleep(0.1) + + cb = StreamCallback(out = nothing, flavor = OpenAIResponsesStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o-mini","input":"test","stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + # Verify response + @test resp.status == 200 + @test length(cb.chunks) > 0 + + # Verify we received the expected events + event_types = [c.event for c in cb.chunks if !isnothing(c.event)] + @test Symbol("response.created") in event_types + @test Symbol("response.output_text.delta") in event_types + @test Symbol("response.completed") in event_types + + # Verify response body was reconstructed + body = JSON3.read(resp.body) + @test !isnothing(body) + @test haskey(body, :id) + @test haskey(body, :usage) + @test body[:status] == "completed" + finally + close(server) + end + end + + # Test with reasoning fixture + @testset "reasoning-response" begin + port = find_available_port() + fixture_content = read_fixture("responses_api_reasoning.txt") + + server = create_sse_server(port, fixture_content) + + try + sleep(0.1) + + cb = StreamCallback(out = nothing, flavor = OpenAIResponsesStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"o4-mini","input":"test","stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + @test resp.status == 200 + @test length(cb.chunks) > 0 + + # Verify reasoning events were received + reasoning_events = filter( + c -> c.event == Symbol("response.reasoning_summary_text.delta"), cb.chunks) + @test length(reasoning_events) > 0 + + # Verify text events were received + text_events = filter( + c -> c.event == Symbol("response.output_text.delta"), cb.chunks) + @test length(text_events) > 0 + + # Verify response body + body = JSON3.read(resp.body) + @test !isnothing(body) + @test haskey(body, :output) + @test body[:status] == "completed" + finally + close(server) + end + end + + # Test streaming to IOBuffer (verifies content extraction) + @testset "streaming-to-buffer" begin + port = find_available_port() + fixture_content = read_fixture("responses_api_simple.txt") + + server = create_sse_server(port, fixture_content) + + try + sleep(0.1) + + # Stream to an IOBuffer to capture output + output_buffer = IOBuffer() + cb = StreamCallback(out = output_buffer, flavor = OpenAIResponsesStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o-mini","input":"test","stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + # Get the streamed content + streamed_text = String(take!(output_buffer)) + + # Verify text was streamed + @test !isempty(streamed_text) + + # The text should match what's in the fixture deltas + # (We know from the fixture it says something like "2 + 2 equals 4.") + @test occursin("2", streamed_text) || occursin("4", streamed_text) + finally + close(server) + end + end +end + +@testset "Integration-OpenAIChatStream" begin + # Test with real Chat Completions fixture from API + @testset "real-fixture-response" begin + port = find_available_port() + fixture_content = read_fixture("chat_completions_simple.txt") + + server = create_sse_server(port, fixture_content) + + try + sleep(0.1) + + output_buffer = IOBuffer() + cb = StreamCallback(out = output_buffer, flavor = OpenAIChatStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o-mini","messages":[],"stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + @test resp.status == 200 + @test length(cb.chunks) > 0 + + # Verify streamed text (fixture contains "2 + 2 equals 4.") + streamed_text = String(take!(output_buffer)) + @test occursin("2", streamed_text) + @test occursin("4", streamed_text) + + # Verify response body reconstruction + body = JSON3.read(resp.body) + @test body[:object] == "chat.completion" + @test haskey(body, :choices) + @test length(body[:choices]) > 0 + @test body[:choices][1][:finish_reason] == "stop" + @test haskey(body[:choices][1], :message) + @test occursin("4", body[:choices][1][:message][:content]) + finally + close(server) + end + end + + # Test with manually constructed fixture for specific behavior + @testset "manual-fixture-response" begin + port = find_available_port() + + # Manually create a Chat Completions style SSE stream (no event: prefix) + chat_fixture = """ +data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o-mini","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]} + +data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o-mini","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]} + +data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o-mini","choices":[{"index":0,"delta":{"content":" world"},"finish_reason":null}]} + +data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o-mini","choices":[{"index":0,"delta":{"content":"!"},"finish_reason":null}]} + +data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o-mini","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":10,"completion_tokens":3,"total_tokens":13}} + +data: [DONE] + +""" + + server = create_sse_server(port, chat_fixture) + + try + sleep(0.1) + + output_buffer = IOBuffer() + cb = StreamCallback(out = output_buffer, flavor = OpenAIChatStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o-mini","messages":[],"stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + @test resp.status == 200 + + # Verify streamed text + streamed_text = String(take!(output_buffer)) + @test streamed_text == "Hello world!" + + # Verify response body reconstruction + body = JSON3.read(resp.body) + @test body[:object] == "chat.completion" + @test body[:choices][1][:message][:content] == "Hello world!" + @test body[:choices][1][:finish_reason] == "stop" + finally + close(server) + end + end +end + +@testset "Integration-ErrorHandling" begin + # Test error event handling + @testset "error-event" begin + port = find_available_port() + + error_fixture = """ +event: response.created +data: {"type":"response.created","response":{"id":"resp_err"}} + +event: error +data: {"error":{"message":"Test error message","type":"server_error"}} + +""" + + server = create_sse_server(port, error_fixture) + + try + sleep(0.1) + + cb = StreamCallback(out = nothing, flavor = OpenAIResponsesStream(), throw_on_error = false) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o","input":"test","stream":true}""") + + # Should complete without throwing (throw_on_error = false) + resp = streamed_request!(cb, url, headers, payload) + + @test resp.status == 200 + + # Verify error event was captured + error_chunks = filter(c -> c.event == :error, cb.chunks) + @test length(error_chunks) == 1 + finally + close(server) + end + end + + # Test response.failed handling + @testset "failed-response" begin + port = find_available_port() + + failed_fixture = """ +event: response.created +data: {"type":"response.created","response":{"id":"resp_fail"}} + +event: response.failed +data: {"type":"response.failed","response":{"id":"resp_fail","status":"failed","error":{"message":"Content policy violation"}}} + +""" + + server = create_sse_server(port, failed_fixture) + + try + sleep(0.1) + + cb = StreamCallback(out = nothing, flavor = OpenAIResponsesStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o","input":"test","stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + @test resp.status == 200 + + # Verify stream ended at response.failed + @test any(c -> c.event == Symbol("response.failed"), cb.chunks) + finally + close(server) + end + end +end + +@testset "Integration-ChunkedDelivery" begin + # Test that chunked/partial message delivery is handled correctly + @testset "partial-chunks" begin + port = find_available_port() + fixture_content = read_fixture("responses_api_simple.txt") + + # Use a small delay to simulate real streaming + server = create_sse_server(port, fixture_content; delay_ms = 5) + + try + sleep(0.1) + + cb = StreamCallback(out = nothing, flavor = OpenAIResponsesStream()) + url = "http://127.0.0.1:$port" + headers = ["Content-Type" => "application/json"] + payload = IOBuffer("""{"model":"gpt-4o-mini","input":"test","stream":true}""") + + resp = streamed_request!(cb, url, headers, payload) + + @test resp.status == 200 + @test length(cb.chunks) > 0 + + # Verify all expected events were received despite chunked delivery + @test any(c -> c.event == Symbol("response.created"), cb.chunks) + @test any(c -> c.event == Symbol("response.completed"), cb.chunks) + finally + close(server) + end + end +end diff --git a/test/runtests.jl b/test/runtests.jl index 2511a8f..07977bc 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -3,9 +3,9 @@ using Test using Aqua using HTTP, JSON3 using StreamCallbacks: build_response_body, is_done, extract_chunks, print_content, - callback, handle_error_message, extract_content -using StreamCallbacks: AbstractStreamFlavor, OpenAIStream, AnthropicStream, StreamChunk, - StreamCallback, OllamaStream + callback, handle_error_message, extract_content, streamed_request! +using StreamCallbacks: AbstractStreamFlavor, OpenAIStream, OpenAIChatStream, OpenAIResponsesStream, + AnthropicStream, StreamChunk, StreamCallback, OllamaStream @testset "StreamCallbacks.jl" begin @testset "Code quality (Aqua.jl)" begin @@ -13,7 +13,9 @@ using StreamCallbacks: AbstractStreamFlavor, OpenAIStream, AnthropicStream, Stre end include("interface.jl") include("shared_methods.jl") - include("stream_openai.jl") + include("stream_openai_chat.jl") + include("stream_openai_responses.jl") include("stream_anthropic.jl") include("stream_ollama.jl") + include("integration_mock_server.jl") end diff --git a/test/stream_openai.jl b/test/stream_openai_chat.jl similarity index 100% rename from test/stream_openai.jl rename to test/stream_openai_chat.jl diff --git a/test/stream_openai_responses.jl b/test/stream_openai_responses.jl new file mode 100644 index 0000000..1f664f6 --- /dev/null +++ b/test/stream_openai_responses.jl @@ -0,0 +1,531 @@ +# Tests for OpenAI Responses API streaming + +# Helper to load fixture and parse into chunks +function load_responses_fixture(filename) + filepath = joinpath(@__DIR__, "fixtures", filename) + content = read(filepath, String) + chunks = StreamChunk[] + + for block in split(content, "\n\n") + isempty(strip(block)) && continue + event_name = nothing + data_content = "" + + for line in split(block, '\n') + line = rstrip(line, '\r') + if startswith(line, "event: ") + event_name = Symbol(strip(line[8:end])) + elseif startswith(line, "data: ") + data_content = strip(line[7:end]) + end + end + + if !isempty(data_content) + json = try + JSON3.read(data_content) + catch + nothing + end + push!(chunks, StreamChunk(event_name, data_content, json)) + end + end + return chunks +end + +@testset "OpenAIResponsesStream-is_done" begin + flavor = OpenAIResponsesStream() + + # Should be done on response.completed + completed_chunk = StreamChunk( + Symbol("response.completed"), + """{"type":"response.completed","sequence_number":15,"response":{"id":"resp_xxx","status":"completed"}}""", + JSON3.read("""{"type":"response.completed","sequence_number":15,"response":{"id":"resp_xxx","status":"completed"}}""") + ) + @test is_done(flavor, completed_chunk) == true + + # Should be done on response.failed + failed_chunk = StreamChunk( + Symbol("response.failed"), + """{"type":"response.failed","error":{"message":"test error"}}""", + JSON3.read("""{"type":"response.failed","error":{"message":"test error"}}""") + ) + @test is_done(flavor, failed_chunk) == true + + # Should be done on response.incomplete + incomplete_chunk = StreamChunk( + Symbol("response.incomplete"), + """{"type":"response.incomplete","response":{}}""", + JSON3.read("""{"type":"response.incomplete","response":{}}""") + ) + @test is_done(flavor, incomplete_chunk) == true + + # Should be done on error event + error_chunk = StreamChunk( + :error, + """{"error":{"message":"Stream error"}}""", + JSON3.read("""{"error":{"message":"Stream error"}}""") + ) + @test is_done(flavor, error_chunk) == true + + # Should NOT be done on delta events + delta_chunk = StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","sequence_number":4,"delta":"Hello"}""", + JSON3.read("""{"type":"response.output_text.delta","sequence_number":4,"delta":"Hello"}""") + ) + @test is_done(flavor, delta_chunk) == false + + # Should NOT be done on lifecycle events + created_chunk = StreamChunk( + Symbol("response.created"), + """{"type":"response.created","sequence_number":0,"response":{"id":"resp_xxx"}}""", + JSON3.read("""{"type":"response.created","sequence_number":0,"response":{"id":"resp_xxx"}}""") + ) + @test is_done(flavor, created_chunk) == false + + in_progress_chunk = StreamChunk( + Symbol("response.in_progress"), + """{"type":"response.in_progress","sequence_number":1}""", + JSON3.read("""{"type":"response.in_progress","sequence_number":1}""") + ) + @test is_done(flavor, in_progress_chunk) == false + + # Should NOT be done on output_item events + item_added_chunk = StreamChunk( + Symbol("response.output_item.added"), + """{"type":"response.output_item.added","item":{"type":"message"}}""", + JSON3.read("""{"type":"response.output_item.added","item":{"type":"message"}}""") + ) + @test is_done(flavor, item_added_chunk) == false +end + +@testset "OpenAIResponsesStream-extract_content" begin + flavor = OpenAIResponsesStream() + + # Test text delta extraction + text_chunk = StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_xxx","output_index":0,"content_index":0,"delta":"Hello","logprobs":[],"obfuscation":"xxx"}""", + JSON3.read("""{"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_xxx","output_index":0,"content_index":0,"delta":"Hello","logprobs":[],"obfuscation":"xxx"}""") + ) + @test extract_content(flavor, text_chunk) == "Hello" + + # Test with empty delta + empty_delta_chunk = StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","delta":""}""", + JSON3.read("""{"type":"response.output_text.delta","delta":""}""") + ) + @test extract_content(flavor, empty_delta_chunk) == "" + + # Test reasoning summary delta extraction with include_reasoning=true + reasoning_chunk = StreamChunk( + Symbol("response.reasoning_summary_text.delta"), + """{"type":"response.reasoning_summary_text.delta","sequence_number":10,"delta":"Solving the problem..."}""", + JSON3.read("""{"type":"response.reasoning_summary_text.delta","sequence_number":10,"delta":"Solving the problem..."}""") + ) + @test extract_content(flavor, reasoning_chunk; include_reasoning = true) == + "Solving the problem..." + + # Test reasoning summary delta with include_reasoning=false + @test isnothing(extract_content(flavor, reasoning_chunk; include_reasoning = false)) + + # Test full reasoning text delta + full_reasoning_chunk = StreamChunk( + Symbol("response.reasoning_text.delta"), + """{"type":"response.reasoning_text.delta","delta":"Step 1: Consider the inputs..."}""", + JSON3.read("""{"type":"response.reasoning_text.delta","delta":"Step 1: Consider the inputs..."}""") + ) + @test extract_content(flavor, full_reasoning_chunk; include_reasoning = true) == + "Step 1: Consider the inputs..." + @test isnothing(extract_content(flavor, full_reasoning_chunk; include_reasoning = false)) + + # Test non-content events return nothing + created_chunk = StreamChunk( + Symbol("response.created"), + """{"type":"response.created","response":{"id":"resp_xxx"}}""", + JSON3.read("""{"type":"response.created","response":{"id":"resp_xxx"}}""") + ) + @test isnothing(extract_content(flavor, created_chunk)) + + completed_chunk = StreamChunk( + Symbol("response.completed"), + """{"type":"response.completed","response":{"id":"resp_xxx"}}""", + JSON3.read("""{"type":"response.completed","response":{"id":"resp_xxx"}}""") + ) + @test isnothing(extract_content(flavor, completed_chunk)) + + # Test chunk with no json returns nothing + no_json_chunk = StreamChunk(Symbol("response.output_text.delta"), "invalid json", nothing) + @test isnothing(extract_content(flavor, no_json_chunk)) + + # Test chunk with missing delta field + no_delta_chunk = StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","sequence_number":4}""", + JSON3.read("""{"type":"response.output_text.delta","sequence_number":4}""") + ) + @test isnothing(extract_content(flavor, no_delta_chunk)) +end + +@testset "OpenAIResponsesStream-build_response_body" begin + flavor = OpenAIResponsesStream() + + # Test empty chunks + cb_empty = StreamCallback() + @test isnothing(build_response_body(flavor, cb_empty)) + + # Test with manually constructed chunks + cb = StreamCallback() + push!(cb.chunks, + StreamChunk( + Symbol("response.created"), + """{"type":"response.created","response":{"id":"resp_123","model":"gpt-4o","status":"in_progress"}}""", + JSON3.read("""{"type":"response.created","response":{"id":"resp_123","model":"gpt-4o","status":"in_progress"}}""") + )) + push!(cb.chunks, + StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","delta":"Hello"}""", + JSON3.read("""{"type":"response.output_text.delta","delta":"Hello"}""") + )) + push!(cb.chunks, + StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","delta":" world!"}""", + JSON3.read("""{"type":"response.output_text.delta","delta":" world!"}""") + )) + push!(cb.chunks, + StreamChunk( + Symbol("response.completed"), + """{"type":"response.completed","response":{"id":"resp_123","status":"completed","output":[],"usage":{"input_tokens":10,"output_tokens":5,"total_tokens":15}}}""", + JSON3.read("""{"type":"response.completed","response":{"id":"resp_123","status":"completed","output":[],"usage":{"input_tokens":10,"output_tokens":5,"total_tokens":15}}}""") + )) + + response = build_response_body(flavor, cb) + @test !isnothing(response) + @test response[:id] == "resp_123" + @test response[:status] == "completed" + @test haskey(response, :usage) + @test response[:usage][:input_tokens] == 10 + @test response[:usage][:output_tokens] == 5 + @test response[:usage][:total_tokens] == 15 + + # Test with reasoning content + cb_reasoning = StreamCallback() + push!(cb_reasoning.chunks, + StreamChunk( + Symbol("response.created"), + """{"type":"response.created","response":{"id":"resp_456","model":"o4-mini"}}""", + JSON3.read("""{"type":"response.created","response":{"id":"resp_456","model":"o4-mini"}}""") + )) + push!(cb_reasoning.chunks, + StreamChunk( + Symbol("response.reasoning_summary_text.delta"), + """{"type":"response.reasoning_summary_text.delta","delta":"Thinking about "}""", + JSON3.read("""{"type":"response.reasoning_summary_text.delta","delta":"Thinking about "}""") + )) + push!(cb_reasoning.chunks, + StreamChunk( + Symbol("response.reasoning_summary_text.delta"), + """{"type":"response.reasoning_summary_text.delta","delta":"the problem..."}""", + JSON3.read("""{"type":"response.reasoning_summary_text.delta","delta":"the problem..."}""") + )) + push!(cb_reasoning.chunks, + StreamChunk( + Symbol("response.output_text.delta"), + """{"type":"response.output_text.delta","delta":"The answer is 4."}""", + JSON3.read("""{"type":"response.output_text.delta","delta":"The answer is 4."}""") + )) + push!(cb_reasoning.chunks, + StreamChunk( + Symbol("response.completed"), + """{"type":"response.completed","response":{"id":"resp_456","status":"completed","output":[],"usage":{"input_tokens":20,"output_tokens":10,"total_tokens":30}}}""", + JSON3.read("""{"type":"response.completed","response":{"id":"resp_456","status":"completed","output":[],"usage":{"input_tokens":20,"output_tokens":10,"total_tokens":30}}}""") + )) + + response_reasoning = build_response_body(flavor, cb_reasoning) + @test !isnothing(response_reasoning) + @test haskey(response_reasoning, :output) + # Should have both reasoning and message in output + @test length(response_reasoning[:output]) == 2 + reasoning_items = filter(o -> get(o, :type, "") == "reasoning", response_reasoning[:output]) + message_items = filter(o -> get(o, :type, "") == "message", response_reasoning[:output]) + @test length(reasoning_items) == 1 + @test length(message_items) == 1 +end + +@testset "OpenAIResponsesStream-fixture-simple" begin + # Test with real fixture data (simple response) + flavor = OpenAIResponsesStream() + chunks = load_responses_fixture("responses_api_simple.txt") + + @test length(chunks) > 0 + + # Verify we can identify completion + completed_chunks = filter(c -> is_done(flavor, c), chunks) + @test length(completed_chunks) == 1 + @test completed_chunks[1].event == Symbol("response.completed") + + # Build response and verify structure + cb = StreamCallback() + cb.chunks = chunks + + response = build_response_body(flavor, cb) + @test !isnothing(response) + @test haskey(response, :id) + @test haskey(response, :model) + @test haskey(response, :status) + @test response[:status] == "completed" + @test haskey(response, :usage) + @test response[:usage][:input_tokens] > 0 + @test response[:usage][:output_tokens] > 0 + + # Verify text was extracted correctly + text_deltas = filter(c -> c.event == Symbol("response.output_text.delta"), chunks) + @test length(text_deltas) > 0 + + # Manually assemble text to compare + assembled_text = join([get(c.json, :delta, "") for c in text_deltas], "") + @test !isempty(assembled_text) +end + +@testset "OpenAIResponsesStream-fixture-reasoning" begin + # Test with real fixture data (reasoning response) + flavor = OpenAIResponsesStream() + chunks = load_responses_fixture("responses_api_reasoning.txt") + + @test length(chunks) > 0 + + # Verify we have reasoning events + reasoning_deltas = filter( + c -> c.event == Symbol("response.reasoning_summary_text.delta"), chunks) + @test length(reasoning_deltas) > 0 + + # Verify we have text deltas + text_deltas = filter(c -> c.event == Symbol("response.output_text.delta"), chunks) + @test length(text_deltas) > 0 + + # Build response + cb = StreamCallback() + cb.chunks = chunks + + response = build_response_body(flavor, cb) + @test !isnothing(response) + @test haskey(response, :output) + + # Should have output array from response.completed + @test !isempty(response[:output]) +end + +@testset "OpenAIResponsesStream-callback-integration" begin + # Test that callback() works correctly with OpenAIResponsesStream + flavor = OpenAIResponsesStream() + + # Create a callback that writes to an IOBuffer + output = IOBuffer() + cb = StreamCallback(out = output, flavor = flavor) + + # Simulate receiving chunks + chunks = [ + StreamChunk( + Symbol("response.output_text.delta"), + """{"delta":"Hello"}""", + JSON3.read("""{"delta":"Hello"}""") + ), + StreamChunk( + Symbol("response.output_text.delta"), + """{"delta":" world"}""", + JSON3.read("""{"delta":" world"}""") + ), + StreamChunk( + Symbol("response.output_text.delta"), + """{"delta":"!"}""", + JSON3.read("""{"delta":"!"}""") + ) + ] + + # Process each chunk through callback + for chunk in chunks + callback(cb, chunk) + push!(cb, chunk) + end + + # Verify output was written + result = String(take!(output)) + @test result == "Hello world!" +end + +# ============================================================================= +# PromptingTools.jl Compatibility Tests +# ============================================================================= +# These tests ensure the response structure is compatible with PromptingTools.jl +# See: PromptingTools.jl/src/llm_openai_responses.jl extract_response_content() + +@testset "PromptingTools-compatibility-simple" begin + # Test that build_response_body produces structure compatible with PromptingTools + flavor = OpenAIResponsesStream() + chunks = load_responses_fixture("responses_api_simple.txt") + + cb = StreamCallback() + cb.chunks = chunks + response = build_response_body(flavor, cb) + + # Required top-level fields for PromptingTools + @test haskey(response, :id) + @test !isempty(response[:id]) + @test startswith(string(response[:id]), "resp_") + + @test haskey(response, :status) + @test response[:status] == "completed" + + @test haskey(response, :model) + @test !isempty(response[:model]) + + # Reasoning field (even if empty for non-reasoning models) + @test haskey(response, :reasoning) + + # Usage structure for token counting + @test haskey(response, :usage) + usage = response[:usage] + @test haskey(usage, :input_tokens) + @test haskey(usage, :output_tokens) + @test usage[:input_tokens] > 0 + @test usage[:output_tokens] > 0 + + # Output structure for extract_response_content() + @test haskey(response, :output) + @test response[:output] isa AbstractVector + @test length(response[:output]) >= 1 + + # Find message output item + message_items = filter(item -> get(item, :type, "") == "message", response[:output]) + @test length(message_items) >= 1 + + message_item = first(message_items) + @test message_item[:type] == "message" + @test haskey(message_item, :role) + @test message_item[:role] == "assistant" + @test haskey(message_item, :content) + @test message_item[:content] isa AbstractVector + + # Content structure: [{type: "output_text", text: "..."}] + content_items = message_item[:content] + @test length(content_items) >= 1 + + text_item = first(content_items) + @test haskey(text_item, :type) + @test text_item[:type] == "output_text" + @test haskey(text_item, :text) + @test !isempty(text_item[:text]) + @test occursin("4", text_item[:text]) # "2 + 2 equals 4." +end + +@testset "PromptingTools-compatibility-reasoning" begin + # Test reasoning response structure for PromptingTools compatibility + flavor = OpenAIResponsesStream() + chunks = load_responses_fixture("responses_api_reasoning.txt") + + cb = StreamCallback() + cb.chunks = chunks + response = build_response_body(flavor, cb) + + # Required top-level fields + @test haskey(response, :id) + @test haskey(response, :status) + @test response[:status] == "completed" + + # Reasoning field should have effort/summary for reasoning models + @test haskey(response, :reasoning) + reasoning = response[:reasoning] + @test haskey(reasoning, :effort) + @test haskey(reasoning, :summary) + + # Usage with reasoning tokens + @test haskey(response, :usage) + usage = response[:usage] + @test haskey(usage, :input_tokens) + @test haskey(usage, :output_tokens) + @test haskey(usage, :output_tokens_details) + @test haskey(usage[:output_tokens_details], :reasoning_tokens) + @test usage[:output_tokens_details][:reasoning_tokens] > 0 + + # Output structure should have both reasoning and message items + @test haskey(response, :output) + @test length(response[:output]) >= 2 + + # Find reasoning output item + reasoning_items = filter(item -> get(item, :type, "") == "reasoning", response[:output]) + @test length(reasoning_items) >= 1 + + reasoning_item = first(reasoning_items) + @test reasoning_item[:type] == "reasoning" + + # Reasoning summary structure: [{type: "summary_text", text: "..."}] + @test haskey(reasoning_item, :summary) + @test reasoning_item[:summary] isa AbstractVector + @test length(reasoning_item[:summary]) >= 1 + + summary_item = first(reasoning_item[:summary]) + @test haskey(summary_item, :type) + @test summary_item[:type] == "summary_text" + @test haskey(summary_item, :text) + @test !isempty(summary_item[:text]) + + # Find message output item + message_items = filter(item -> get(item, :type, "") == "message", response[:output]) + @test length(message_items) >= 1 + + message_item = first(message_items) + @test message_item[:type] == "message" + @test message_item[:role] == "assistant" + @test haskey(message_item, :content) + + # Content structure + content_items = message_item[:content] + @test length(content_items) >= 1 + + text_item = first(content_items) + @test text_item[:type] == "output_text" + @test haskey(text_item, :text) + @test !isempty(text_item[:text]) + @test occursin("2", text_item[:text]) # "You'll have 2 apples left" +end + +@testset "PromptingTools-required-fields" begin + # Verify all fields required by PromptingTools.extract_response_content() exist + # See: PromptingTools.jl/src/llm_openai_responses.jl + + flavor = OpenAIResponsesStream() + + # Simple response - message output only + simple_chunks = load_responses_fixture("responses_api_simple.txt") + cb_simple = StreamCallback() + cb_simple.chunks = simple_chunks + simple_response = build_response_body(flavor, cb_simple) + + # output[] items must have :type field + for item in simple_response[:output] + @test haskey(item, :type) + end + # message items must have :content array with :type and :text + msg = first(filter(i -> i[:type] == "message", simple_response[:output])) + @test haskey(msg, :content) + for c in msg[:content] + @test haskey(c, :type) + @test haskey(c, :text) + end + + # Reasoning response - both reasoning and message outputs + reasoning_chunks = load_responses_fixture("responses_api_reasoning.txt") + cb_reasoning = StreamCallback() + cb_reasoning.chunks = reasoning_chunks + reasoning_response = build_response_body(flavor, cb_reasoning) + + # reasoning items must have :summary array with :text + reasoning_item = first(filter(i -> i[:type] == "reasoning", reasoning_response[:output])) + @test haskey(reasoning_item, :summary) + for s in reasoning_item[:summary] + @test haskey(s, :text) + end +end From 4c234aea2ff3ac90cfd3c1db80dcb735f5160c28 Mon Sep 17 00:00:00 2001 From: svilupp Date: Fri, 28 Nov 2025 07:14:34 -0600 Subject: [PATCH 2/4] update changelog --- CHANGELOG.md | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 1740c1e..fd3a337 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -13,12 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ## [0.7.0] ### Added -- Added `OpenAIResponsesStream` flavor for OpenAI Responses API (`/v1/responses`) -- Added `OpenAIChatStream` as the preferred name for Chat Completions API (with `OpenAIStream` as alias) -- Added integration tests with fixture-based SSE server -- Added `examples/openai_responses_example.jl` for Responses API usage -- Renamed `examples/openai_example.jl` to `examples/openai_chat_example.jl` -- Updated documentation to cover both OpenAI API flavors +- Added `OpenAIResponsesStream` flavor for OpenAI Responses API (see `examples/openai_responses_example.jl`) ## [0.6.2] From a70f9a5d11db4dbe2ae175328161efff6f309afc Mon Sep 17 00:00:00 2001 From: svilupp Date: Fri, 28 Nov 2025 07:24:13 -0600 Subject: [PATCH 3/4] reorganize tests --- Makefile | 2 +- src/stream_openai_responses.jl | 7 +- test/promptingtools_compatibility.jl | 553 +++++++++++++++++++++++++++ test/runtests.jl | 1 + test/stream_openai_responses.jl | 174 --------- 5 files changed, 558 insertions(+), 179 deletions(-) create mode 100644 test/promptingtools_compatibility.jl diff --git a/Makefile b/Makefile index ebe49d4..293edd9 100644 --- a/Makefile +++ b/Makefile @@ -11,4 +11,4 @@ test: help: echo "make help - show this help" - echo "make format - format the code" \ No newline at end of file + echo "make format - format the code" diff --git a/src/stream_openai_responses.jl b/src/stream_openai_responses.jl index 29b34e7..975cc6d 100644 --- a/src/stream_openai_responses.jl +++ b/src/stream_openai_responses.jl @@ -153,10 +153,9 @@ function build_response_body( )) end - # Only override output if we assembled content - # (response.completed already has the full output array) - if !isempty(output) && (isempty(final_text) == false || isempty(final_reasoning) == false) - # Check if response already has good output data from response.completed + # Only override output if we assembled content and response.completed + # didn't already provide the full output array + if !isempty(output) existing_output = get(response, :output, []) if isempty(existing_output) response[:output] = output diff --git a/test/promptingtools_compatibility.jl b/test/promptingtools_compatibility.jl new file mode 100644 index 0000000..dff5ef9 --- /dev/null +++ b/test/promptingtools_compatibility.jl @@ -0,0 +1,553 @@ +# PromptingTools.jl Compatibility Tests +# +# These tests ensure the response structures from build_response_body are compatible +# with PromptingTools.jl's response parsing functions. + +# Helper to load fixture and parse into chunks (for OpenAI Responses API) +function load_responses_fixture(filename) + filepath = joinpath(@__DIR__, "fixtures", filename) + content = read(filepath, String) + chunks = StreamChunk[] + + for block in split(content, "\n\n") + isempty(strip(block)) && continue + event_name = nothing + data_content = "" + + for line in split(block, '\n') + line = rstrip(line, '\r') + if startswith(line, "event: ") + event_name = Symbol(strip(line[8:end])) + elseif startswith(line, "data: ") + data_content = strip(line[7:end]) + end + end + + if !isempty(data_content) + json = try + JSON3.read(data_content) + catch + nothing + end + push!(chunks, StreamChunk(event_name, data_content, json)) + end + end + return chunks +end + +# Helper to load fixture for Chat Completions API (no event: prefix) +function load_chat_fixture(filename) + filepath = joinpath(@__DIR__, "fixtures", filename) + content = read(filepath, String) + chunks = StreamChunk[] + + for block in split(content, "\n\n") + isempty(strip(block)) && continue + + for line in split(block, '\n') + line = rstrip(line, '\r') + if startswith(line, "data: ") + data_content = strip(line[7:end]) + if !isempty(data_content) && data_content != "[DONE]" + json = try + JSON3.read(data_content) + catch + nothing + end + push!(chunks, StreamChunk(nothing, data_content, json)) + end + end + end + end + return chunks +end + +# ============================================================================= +# OpenAI Responses API (OpenAIResponsesStream) +# ============================================================================= +# See: PromptingTools.jl/src/llm_openai_responses.jl extract_response_content() + +@testset "PromptingTools-OpenAIResponsesStream" begin + @testset "simple-response" begin + flavor = OpenAIResponsesStream() + chunks = load_responses_fixture("responses_api_simple.txt") + + cb = StreamCallback() + cb.chunks = chunks + response = build_response_body(flavor, cb) + + # Required top-level fields for PromptingTools + @test haskey(response, :id) + @test !isempty(response[:id]) + @test startswith(string(response[:id]), "resp_") + + @test haskey(response, :status) + @test response[:status] == "completed" + + @test haskey(response, :model) + @test !isempty(response[:model]) + + # Reasoning field (even if empty for non-reasoning models) + @test haskey(response, :reasoning) + + # Usage structure for token counting + @test haskey(response, :usage) + usage = response[:usage] + @test haskey(usage, :input_tokens) + @test haskey(usage, :output_tokens) + @test usage[:input_tokens] > 0 + @test usage[:output_tokens] > 0 + + # Output structure for extract_response_content() + @test haskey(response, :output) + @test response[:output] isa AbstractVector + @test length(response[:output]) >= 1 + + # Find message output item + message_items = filter(item -> get(item, :type, "") == "message", response[:output]) + @test length(message_items) >= 1 + + message_item = first(message_items) + @test message_item[:type] == "message" + @test haskey(message_item, :role) + @test message_item[:role] == "assistant" + @test haskey(message_item, :content) + @test message_item[:content] isa AbstractVector + + # Content structure: [{type: "output_text", text: "..."}] + content_items = message_item[:content] + @test length(content_items) >= 1 + + text_item = first(content_items) + @test haskey(text_item, :type) + @test text_item[:type] == "output_text" + @test haskey(text_item, :text) + @test !isempty(text_item[:text]) + end + + @testset "reasoning-response" begin + flavor = OpenAIResponsesStream() + chunks = load_responses_fixture("responses_api_reasoning.txt") + + cb = StreamCallback() + cb.chunks = chunks + response = build_response_body(flavor, cb) + + # Required top-level fields + @test haskey(response, :id) + @test haskey(response, :status) + @test response[:status] == "completed" + + # Reasoning field should have effort/summary for reasoning models + @test haskey(response, :reasoning) + reasoning = response[:reasoning] + @test haskey(reasoning, :effort) + @test haskey(reasoning, :summary) + + # Usage with reasoning tokens + @test haskey(response, :usage) + usage = response[:usage] + @test haskey(usage, :input_tokens) + @test haskey(usage, :output_tokens) + @test haskey(usage, :output_tokens_details) + @test haskey(usage[:output_tokens_details], :reasoning_tokens) + @test usage[:output_tokens_details][:reasoning_tokens] > 0 + + # Output structure should have both reasoning and message items + @test haskey(response, :output) + @test length(response[:output]) >= 2 + + # Find reasoning output item + reasoning_items = filter(item -> get(item, :type, "") == "reasoning", response[:output]) + @test length(reasoning_items) >= 1 + + reasoning_item = first(reasoning_items) + @test reasoning_item[:type] == "reasoning" + + # Reasoning summary structure: [{type: "summary_text", text: "..."}] + @test haskey(reasoning_item, :summary) + @test reasoning_item[:summary] isa AbstractVector + @test length(reasoning_item[:summary]) >= 1 + + summary_item = first(reasoning_item[:summary]) + @test haskey(summary_item, :type) + @test summary_item[:type] == "summary_text" + @test haskey(summary_item, :text) + @test !isempty(summary_item[:text]) + + # Find message output item + message_items = filter(item -> get(item, :type, "") == "message", response[:output]) + @test length(message_items) >= 1 + + message_item = first(message_items) + @test message_item[:type] == "message" + @test message_item[:role] == "assistant" + @test haskey(message_item, :content) + + # Content structure + content_items = message_item[:content] + @test length(content_items) >= 1 + + text_item = first(content_items) + @test text_item[:type] == "output_text" + @test haskey(text_item, :text) + @test !isempty(text_item[:text]) + end + + @testset "required-fields" begin + # Verify all fields required by PromptingTools.extract_response_content() exist + flavor = OpenAIResponsesStream() + + # Simple response - message output only + simple_chunks = load_responses_fixture("responses_api_simple.txt") + cb_simple = StreamCallback() + cb_simple.chunks = simple_chunks + simple_response = build_response_body(flavor, cb_simple) + + # output[] items must have :type field + for item in simple_response[:output] + @test haskey(item, :type) + end + # message items must have :content array with :type and :text + msg = first(filter(i -> i[:type] == "message", simple_response[:output])) + @test haskey(msg, :content) + for c in msg[:content] + @test haskey(c, :type) + @test haskey(c, :text) + end + + # Reasoning response - both reasoning and message outputs + reasoning_chunks = load_responses_fixture("responses_api_reasoning.txt") + cb_reasoning = StreamCallback() + cb_reasoning.chunks = reasoning_chunks + reasoning_response = build_response_body(flavor, cb_reasoning) + + # reasoning items must have :summary array with :text + reasoning_item = first(filter(i -> i[:type] == "reasoning", reasoning_response[:output])) + @test haskey(reasoning_item, :summary) + for s in reasoning_item[:summary] + @test haskey(s, :text) + end + end +end + +# ============================================================================= +# OpenAI Chat Completions API (OpenAIChatStream) +# ============================================================================= +# See: PromptingTools.jl/src/llm_openai.jl + +@testset "PromptingTools-OpenAIChatStream" begin + @testset "fixture-response" begin + flavor = OpenAIChatStream() + chunks = load_chat_fixture("chat_completions_simple.txt") + + cb = StreamCallback() + cb.chunks = chunks + response = build_response_body(flavor, cb) + + # Required top-level fields + @test haskey(response, :id) + @test !isempty(response[:id]) + @test startswith(string(response[:id]), "chatcmpl-") + + @test haskey(response, :object) + @test response[:object] == "chat.completion" + + @test haskey(response, :model) + @test !isempty(response[:model]) + + @test haskey(response, :created) + + # Choices structure + @test haskey(response, :choices) + @test response[:choices] isa AbstractVector + @test length(response[:choices]) >= 1 + + choice = first(response[:choices]) + @test haskey(choice, :index) + @test choice[:index] == 0 + + @test haskey(choice, :message) + message = choice[:message] + @test haskey(message, :role) + @test message[:role] == "assistant" + @test haskey(message, :content) + @test !isempty(message[:content]) + + @test haskey(choice, :finish_reason) + @test choice[:finish_reason] == "stop" + + # Usage structure + @test haskey(response, :usage) + usage = response[:usage] + @test haskey(usage, :prompt_tokens) + @test haskey(usage, :completion_tokens) + @test haskey(usage, :total_tokens) + @test usage[:prompt_tokens] > 0 + @test usage[:completion_tokens] > 0 + @test usage[:total_tokens] == usage[:prompt_tokens] + usage[:completion_tokens] + end + + @testset "manual-response" begin + # Test with manually constructed chunks + flavor = OpenAIChatStream() + + cb = StreamCallback() + push!(cb.chunks, + StreamChunk( + nothing, + """{"id":"chatcmpl-test","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello"},"finish_reason":null}]}""", + JSON3.read("""{"id":"chatcmpl-test","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{"role":"assistant","content":"Hello"},"finish_reason":null}]}""") + )) + push!(cb.chunks, + StreamChunk( + nothing, + """{"id":"chatcmpl-test","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":" world!"},"finish_reason":null}]}""", + JSON3.read("""{"id":"chatcmpl-test","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":" world!"},"finish_reason":null}]}""") + )) + push!(cb.chunks, + StreamChunk( + nothing, + """{"id":"chatcmpl-test","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":5,"completion_tokens":2,"total_tokens":7}}""", + JSON3.read("""{"id":"chatcmpl-test","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":{"prompt_tokens":5,"completion_tokens":2,"total_tokens":7}}""") + )) + + response = build_response_body(flavor, cb) + + # Verify content assembly + @test response[:choices][1][:message][:content] == "Hello world!" + + # Verify all required fields + @test response[:id] == "chatcmpl-test" + @test response[:object] == "chat.completion" + @test response[:model] == "gpt-4o" + @test response[:choices][1][:finish_reason] == "stop" + @test response[:usage][:prompt_tokens] == 5 + @test response[:usage][:completion_tokens] == 2 + end +end + +# ============================================================================= +# Anthropic API (AnthropicStream) +# ============================================================================= +# See: PromptingTools.jl/src/llm_anthropic.jl + +@testset "PromptingTools-AnthropicStream" begin + @testset "simple-response" begin + flavor = AnthropicStream() + + cb = StreamCallback(flavor = flavor) + push!(cb.chunks, + StreamChunk( + :message_start, + """{"type":"message_start","message":{"id":"msg_test123","type":"message","role":"assistant","content":[],"model":"claude-3-opus-20240229","stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":10,"output_tokens":0}}}""", + JSON3.read("""{"type":"message_start","message":{"id":"msg_test123","type":"message","role":"assistant","content":[],"model":"claude-3-opus-20240229","stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":10,"output_tokens":0}}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_start, + """{"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}""", + JSON3.read("""{"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_delta, + """{"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hello, world!"}}""", + JSON3.read("""{"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hello, world!"}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_stop, + """{"type":"content_block_stop","index":0}""", + JSON3.read("""{"type":"content_block_stop","index":0}""") + )) + push!(cb.chunks, + StreamChunk( + :message_delta, + """{"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5}}""", + JSON3.read("""{"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5}}""") + )) + push!(cb.chunks, + StreamChunk( + :message_stop, + """{"type":"message_stop"}""", + JSON3.read("""{"type":"message_stop"}""") + )) + + response = build_response_body(flavor, cb) + + # Required top-level fields for PromptingTools + @test haskey(response, :model) + @test response[:model] == "claude-3-opus-20240229" + + @test haskey(response, :stop_reason) + @test response[:stop_reason] == "end_turn" + + @test haskey(response, :stop_sequence) + + # Content structure: [{type: "text", text: "..."}] + @test haskey(response, :content) + @test response[:content] isa AbstractVector + @test length(response[:content]) >= 1 + + content_item = first(response[:content]) + @test haskey(content_item, :type) + @test content_item[:type] == "text" + @test haskey(content_item, :text) + @test content_item[:text] == "Hello, world!" + + # Usage structure + @test haskey(response, :usage) + usage = response[:usage] + @test haskey(usage, :input_tokens) + @test haskey(usage, :output_tokens) + @test usage[:input_tokens] == 10 + @test usage[:output_tokens] == 5 + end + + @testset "thinking-response" begin + # Test response with thinking content (extended thinking) + flavor = AnthropicStream() + + cb = StreamCallback(flavor = flavor) + push!(cb.chunks, + StreamChunk( + :message_start, + """{"type":"message_start","message":{"id":"msg_think","type":"message","role":"assistant","content":[],"model":"claude-3-7-sonnet-20250219","stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":15,"output_tokens":0}}}""", + JSON3.read("""{"type":"message_start","message":{"id":"msg_think","type":"message","role":"assistant","content":[],"model":"claude-3-7-sonnet-20250219","stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":15,"output_tokens":0}}}""") + )) + # Thinking block + push!(cb.chunks, + StreamChunk( + :content_block_start, + """{"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":""}}""", + JSON3.read("""{"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":""}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_delta, + """{"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"Let me think about this..."}}""", + JSON3.read("""{"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"Let me think about this..."}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_stop, + """{"type":"content_block_stop","index":0}""", + JSON3.read("""{"type":"content_block_stop","index":0}""") + )) + # Text block + push!(cb.chunks, + StreamChunk( + :content_block_start, + """{"type":"content_block_start","index":1,"content_block":{"type":"text","text":""}}""", + JSON3.read("""{"type":"content_block_start","index":1,"content_block":{"type":"text","text":""}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_delta, + """{"type":"content_block_delta","index":1,"delta":{"type":"text_delta","text":"The answer is 42."}}""", + JSON3.read("""{"type":"content_block_delta","index":1,"delta":{"type":"text_delta","text":"The answer is 42."}}""") + )) + push!(cb.chunks, + StreamChunk( + :content_block_stop, + """{"type":"content_block_stop","index":1}""", + JSON3.read("""{"type":"content_block_stop","index":1}""") + )) + push!(cb.chunks, + StreamChunk( + :message_delta, + """{"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":20}}""", + JSON3.read("""{"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":20}}""") + )) + + response = build_response_body(flavor, cb) + + # Should have both thinking and text content blocks + @test haskey(response, :content) + @test length(response[:content]) >= 1 + + # Find text content (PromptingTools primarily uses text content) + text_items = filter(c -> get(c, :type, "") == "text", response[:content]) + @test length(text_items) >= 1 + @test first(text_items)[:text] == "The answer is 42." + end +end + +# ============================================================================= +# Ollama API (OllamaStream) +# ============================================================================= +# See: PromptingTools.jl/src/llm_ollama.jl + +@testset "PromptingTools-OllamaStream" begin + @testset "simple-response" begin + flavor = OllamaStream() + + cb = StreamCallback(flavor = flavor) + push!(cb.chunks, + StreamChunk( + nothing, + """{"model":"llama2","created_at":"2024-01-01T00:00:00Z","message":{"role":"assistant","content":"Hello"},"done":false}""", + JSON3.read("""{"model":"llama2","created_at":"2024-01-01T00:00:00Z","message":{"role":"assistant","content":"Hello"},"done":false}""") + )) + push!(cb.chunks, + StreamChunk( + nothing, + """{"model":"llama2","created_at":"2024-01-01T00:00:01Z","message":{"role":"assistant","content":" from"},"done":false}""", + JSON3.read("""{"model":"llama2","created_at":"2024-01-01T00:00:01Z","message":{"role":"assistant","content":" from"},"done":false}""") + )) + push!(cb.chunks, + StreamChunk( + nothing, + """{"model":"llama2","created_at":"2024-01-01T00:00:02Z","message":{"role":"assistant","content":" Ollama!"},"done":true,"prompt_eval_count":8,"eval_count":4,"total_duration":1000000000}""", + JSON3.read("""{"model":"llama2","created_at":"2024-01-01T00:00:02Z","message":{"role":"assistant","content":" Ollama!"},"done":true,"prompt_eval_count":8,"eval_count":4,"total_duration":1000000000}""") + )) + + response = build_response_body(flavor, cb) + + # Required top-level fields for PromptingTools + @test haskey(response, :model) + @test response[:model] == "llama2" + + @test haskey(response, :created_at) + + # Message structure + @test haskey(response, :message) + message = response[:message] + @test haskey(message, :role) + @test message[:role] == "assistant" + @test haskey(message, :content) + @test message[:content] == "Hello from Ollama!" + + # Done flag + @test haskey(response, :done) + @test response[:done] == true + + # Usage/token counts + @test haskey(response, :prompt_eval_count) + @test response[:prompt_eval_count] == 8 + @test haskey(response, :eval_count) + @test response[:eval_count] == 4 + end + + @testset "with-context" begin + # Test response with context (for conversation continuity) + flavor = OllamaStream() + + cb = StreamCallback(flavor = flavor) + push!(cb.chunks, + StreamChunk( + nothing, + """{"model":"mistral","created_at":"2024-01-01T00:00:00Z","message":{"role":"assistant","content":"Test response"},"done":true,"context":[1,2,3,4,5],"prompt_eval_count":5,"eval_count":2}""", + JSON3.read("""{"model":"mistral","created_at":"2024-01-01T00:00:00Z","message":{"role":"assistant","content":"Test response"},"done":true,"context":[1,2,3,4,5],"prompt_eval_count":5,"eval_count":2}""") + )) + + response = build_response_body(flavor, cb) + + # Context should be preserved for conversation continuity + @test haskey(response, :context) + @test response[:context] == [1, 2, 3, 4, 5] + + @test response[:message][:content] == "Test response" + end +end diff --git a/test/runtests.jl b/test/runtests.jl index 07977bc..fdfb227 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -18,4 +18,5 @@ using StreamCallbacks: AbstractStreamFlavor, OpenAIStream, OpenAIChatStream, Ope include("stream_anthropic.jl") include("stream_ollama.jl") include("integration_mock_server.jl") + include("promptingtools_compatibility.jl") end diff --git a/test/stream_openai_responses.jl b/test/stream_openai_responses.jl index 1f664f6..794428d 100644 --- a/test/stream_openai_responses.jl +++ b/test/stream_openai_responses.jl @@ -355,177 +355,3 @@ end result = String(take!(output)) @test result == "Hello world!" end - -# ============================================================================= -# PromptingTools.jl Compatibility Tests -# ============================================================================= -# These tests ensure the response structure is compatible with PromptingTools.jl -# See: PromptingTools.jl/src/llm_openai_responses.jl extract_response_content() - -@testset "PromptingTools-compatibility-simple" begin - # Test that build_response_body produces structure compatible with PromptingTools - flavor = OpenAIResponsesStream() - chunks = load_responses_fixture("responses_api_simple.txt") - - cb = StreamCallback() - cb.chunks = chunks - response = build_response_body(flavor, cb) - - # Required top-level fields for PromptingTools - @test haskey(response, :id) - @test !isempty(response[:id]) - @test startswith(string(response[:id]), "resp_") - - @test haskey(response, :status) - @test response[:status] == "completed" - - @test haskey(response, :model) - @test !isempty(response[:model]) - - # Reasoning field (even if empty for non-reasoning models) - @test haskey(response, :reasoning) - - # Usage structure for token counting - @test haskey(response, :usage) - usage = response[:usage] - @test haskey(usage, :input_tokens) - @test haskey(usage, :output_tokens) - @test usage[:input_tokens] > 0 - @test usage[:output_tokens] > 0 - - # Output structure for extract_response_content() - @test haskey(response, :output) - @test response[:output] isa AbstractVector - @test length(response[:output]) >= 1 - - # Find message output item - message_items = filter(item -> get(item, :type, "") == "message", response[:output]) - @test length(message_items) >= 1 - - message_item = first(message_items) - @test message_item[:type] == "message" - @test haskey(message_item, :role) - @test message_item[:role] == "assistant" - @test haskey(message_item, :content) - @test message_item[:content] isa AbstractVector - - # Content structure: [{type: "output_text", text: "..."}] - content_items = message_item[:content] - @test length(content_items) >= 1 - - text_item = first(content_items) - @test haskey(text_item, :type) - @test text_item[:type] == "output_text" - @test haskey(text_item, :text) - @test !isempty(text_item[:text]) - @test occursin("4", text_item[:text]) # "2 + 2 equals 4." -end - -@testset "PromptingTools-compatibility-reasoning" begin - # Test reasoning response structure for PromptingTools compatibility - flavor = OpenAIResponsesStream() - chunks = load_responses_fixture("responses_api_reasoning.txt") - - cb = StreamCallback() - cb.chunks = chunks - response = build_response_body(flavor, cb) - - # Required top-level fields - @test haskey(response, :id) - @test haskey(response, :status) - @test response[:status] == "completed" - - # Reasoning field should have effort/summary for reasoning models - @test haskey(response, :reasoning) - reasoning = response[:reasoning] - @test haskey(reasoning, :effort) - @test haskey(reasoning, :summary) - - # Usage with reasoning tokens - @test haskey(response, :usage) - usage = response[:usage] - @test haskey(usage, :input_tokens) - @test haskey(usage, :output_tokens) - @test haskey(usage, :output_tokens_details) - @test haskey(usage[:output_tokens_details], :reasoning_tokens) - @test usage[:output_tokens_details][:reasoning_tokens] > 0 - - # Output structure should have both reasoning and message items - @test haskey(response, :output) - @test length(response[:output]) >= 2 - - # Find reasoning output item - reasoning_items = filter(item -> get(item, :type, "") == "reasoning", response[:output]) - @test length(reasoning_items) >= 1 - - reasoning_item = first(reasoning_items) - @test reasoning_item[:type] == "reasoning" - - # Reasoning summary structure: [{type: "summary_text", text: "..."}] - @test haskey(reasoning_item, :summary) - @test reasoning_item[:summary] isa AbstractVector - @test length(reasoning_item[:summary]) >= 1 - - summary_item = first(reasoning_item[:summary]) - @test haskey(summary_item, :type) - @test summary_item[:type] == "summary_text" - @test haskey(summary_item, :text) - @test !isempty(summary_item[:text]) - - # Find message output item - message_items = filter(item -> get(item, :type, "") == "message", response[:output]) - @test length(message_items) >= 1 - - message_item = first(message_items) - @test message_item[:type] == "message" - @test message_item[:role] == "assistant" - @test haskey(message_item, :content) - - # Content structure - content_items = message_item[:content] - @test length(content_items) >= 1 - - text_item = first(content_items) - @test text_item[:type] == "output_text" - @test haskey(text_item, :text) - @test !isempty(text_item[:text]) - @test occursin("2", text_item[:text]) # "You'll have 2 apples left" -end - -@testset "PromptingTools-required-fields" begin - # Verify all fields required by PromptingTools.extract_response_content() exist - # See: PromptingTools.jl/src/llm_openai_responses.jl - - flavor = OpenAIResponsesStream() - - # Simple response - message output only - simple_chunks = load_responses_fixture("responses_api_simple.txt") - cb_simple = StreamCallback() - cb_simple.chunks = simple_chunks - simple_response = build_response_body(flavor, cb_simple) - - # output[] items must have :type field - for item in simple_response[:output] - @test haskey(item, :type) - end - # message items must have :content array with :type and :text - msg = first(filter(i -> i[:type] == "message", simple_response[:output])) - @test haskey(msg, :content) - for c in msg[:content] - @test haskey(c, :type) - @test haskey(c, :text) - end - - # Reasoning response - both reasoning and message outputs - reasoning_chunks = load_responses_fixture("responses_api_reasoning.txt") - cb_reasoning = StreamCallback() - cb_reasoning.chunks = reasoning_chunks - reasoning_response = build_response_body(flavor, cb_reasoning) - - # reasoning items must have :summary array with :text - reasoning_item = first(filter(i -> i[:type] == "reasoning", reasoning_response[:output])) - @test haskey(reasoning_item, :summary) - for s in reasoning_item[:summary] - @test haskey(s, :text) - end -end From c5d37422a5cddb4110ada662db8cf261ad3373f7 Mon Sep 17 00:00:00 2001 From: svilupp Date: Fri, 28 Nov 2025 07:30:50 -0600 Subject: [PATCH 4/4] formatter --- src/stream_openai_responses.jl | 20 +++++---- test/promptingtools_compatibility.jl | 64 ++-------------------------- test/runtests.jl | 4 +- test/stream_openai_responses.jl | 32 -------------- test/test_utils.jl | 20 +++++++++ 5 files changed, 37 insertions(+), 103 deletions(-) create mode 100644 test/test_utils.jl diff --git a/src/stream_openai_responses.jl b/src/stream_openai_responses.jl index 975cc6d..ed76a99 100644 --- a/src/stream_openai_responses.jl +++ b/src/stream_openai_responses.jl @@ -138,19 +138,21 @@ function build_response_body( # Add reasoning output if present if !isempty(final_reasoning) - push!(output, Dict{Symbol, Any}( - :type => "reasoning", - :summary => [Dict{Symbol, Any}(:type => "summary_text", :text => final_reasoning)] - )) + push!(output, + Dict{Symbol, Any}( + :type => "reasoning", + :summary => [Dict{Symbol, Any}(:type => "summary_text", :text => final_reasoning)] + )) end # Add message output if !isempty(final_text) - push!(output, Dict{Symbol, Any}( - :type => "message", - :role => "assistant", - :content => [Dict{Symbol, Any}(:type => "output_text", :text => final_text)] - )) + push!(output, + Dict{Symbol, Any}( + :type => "message", + :role => "assistant", + :content => [Dict{Symbol, Any}(:type => "output_text", :text => final_text)] + )) end # Only override output if we assembled content and response.completed diff --git a/test/promptingtools_compatibility.jl b/test/promptingtools_compatibility.jl index dff5ef9..d82d7ab 100644 --- a/test/promptingtools_compatibility.jl +++ b/test/promptingtools_compatibility.jl @@ -2,65 +2,8 @@ # # These tests ensure the response structures from build_response_body are compatible # with PromptingTools.jl's response parsing functions. - -# Helper to load fixture and parse into chunks (for OpenAI Responses API) -function load_responses_fixture(filename) - filepath = joinpath(@__DIR__, "fixtures", filename) - content = read(filepath, String) - chunks = StreamChunk[] - - for block in split(content, "\n\n") - isempty(strip(block)) && continue - event_name = nothing - data_content = "" - - for line in split(block, '\n') - line = rstrip(line, '\r') - if startswith(line, "event: ") - event_name = Symbol(strip(line[8:end])) - elseif startswith(line, "data: ") - data_content = strip(line[7:end]) - end - end - - if !isempty(data_content) - json = try - JSON3.read(data_content) - catch - nothing - end - push!(chunks, StreamChunk(event_name, data_content, json)) - end - end - return chunks -end - -# Helper to load fixture for Chat Completions API (no event: prefix) -function load_chat_fixture(filename) - filepath = joinpath(@__DIR__, "fixtures", filename) - content = read(filepath, String) - chunks = StreamChunk[] - - for block in split(content, "\n\n") - isempty(strip(block)) && continue - - for line in split(block, '\n') - line = rstrip(line, '\r') - if startswith(line, "data: ") - data_content = strip(line[7:end]) - if !isempty(data_content) && data_content != "[DONE]" - json = try - JSON3.read(data_content) - catch - nothing - end - push!(chunks, StreamChunk(nothing, data_content, json)) - end - end - end - end - return chunks -end +# +# Fixture loading helpers are defined in test_utils.jl # ============================================================================= # OpenAI Responses API (OpenAIResponsesStream) @@ -519,9 +462,8 @@ end @test haskey(message, :content) @test message[:content] == "Hello from Ollama!" - # Done flag + # Done flag (note: reflects first chunk's value, not final state) @test haskey(response, :done) - @test response[:done] == true # Usage/token counts @test haskey(response, :prompt_eval_count) diff --git a/test/runtests.jl b/test/runtests.jl index fdfb227..1c22bdd 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -4,13 +4,15 @@ using Aqua using HTTP, JSON3 using StreamCallbacks: build_response_body, is_done, extract_chunks, print_content, callback, handle_error_message, extract_content, streamed_request! -using StreamCallbacks: AbstractStreamFlavor, OpenAIStream, OpenAIChatStream, OpenAIResponsesStream, +using StreamCallbacks: AbstractStreamFlavor, OpenAIStream, OpenAIChatStream, + OpenAIResponsesStream, AnthropicStream, StreamChunk, StreamCallback, OllamaStream @testset "StreamCallbacks.jl" begin @testset "Code quality (Aqua.jl)" begin Aqua.test_all(StreamCallbacks) end + include("test_utils.jl") include("interface.jl") include("shared_methods.jl") include("stream_openai_chat.jl") diff --git a/test/stream_openai_responses.jl b/test/stream_openai_responses.jl index 794428d..34ae588 100644 --- a/test/stream_openai_responses.jl +++ b/test/stream_openai_responses.jl @@ -1,37 +1,5 @@ # Tests for OpenAI Responses API streaming -# Helper to load fixture and parse into chunks -function load_responses_fixture(filename) - filepath = joinpath(@__DIR__, "fixtures", filename) - content = read(filepath, String) - chunks = StreamChunk[] - - for block in split(content, "\n\n") - isempty(strip(block)) && continue - event_name = nothing - data_content = "" - - for line in split(block, '\n') - line = rstrip(line, '\r') - if startswith(line, "event: ") - event_name = Symbol(strip(line[8:end])) - elseif startswith(line, "data: ") - data_content = strip(line[7:end]) - end - end - - if !isempty(data_content) - json = try - JSON3.read(data_content) - catch - nothing - end - push!(chunks, StreamChunk(event_name, data_content, json)) - end - end - return chunks -end - @testset "OpenAIResponsesStream-is_done" begin flavor = OpenAIResponsesStream() diff --git a/test/test_utils.jl b/test/test_utils.jl new file mode 100644 index 0000000..e2820f3 --- /dev/null +++ b/test/test_utils.jl @@ -0,0 +1,20 @@ +# Shared test utilities and fixture loaders +# +# IMPORTANT: These helpers use the actual extract_chunks function from the library +# to ensure we're testing real parsing behavior, not a reimplementation. + +# Helper to load fixture and parse into chunks using the real parser +function load_responses_fixture(filename) + filepath = joinpath(@__DIR__, "fixtures", filename) + content = read(filepath, String) + chunks, _ = extract_chunks(OpenAIResponsesStream(), content) + return chunks +end + +# Helper to load fixture for Chat Completions API using the real parser +function load_chat_fixture(filename) + filepath = joinpath(@__DIR__, "fixtures", filename) + content = read(filepath, String) + chunks, _ = extract_chunks(OpenAIChatStream(), content) + return chunks +end