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14 changed files with 50 additions and 205 deletions

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@ -48,8 +48,6 @@ jobs:
target: aarch64
- runner: ubuntu-22.04
target: armv7
- runner: ubuntu-22.04
target: ppc64le
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5

3
.gitignore vendored
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@ -70,6 +70,3 @@ docs/_build/
# Pyenv
.python-version
# Avoid ignoring shadcn utils
!demo/harmony-demo/src/lib

2
Cargo.lock generated
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@ -1317,7 +1317,7 @@ checksum = "42f5e15c9953c5e4ccceeb2e7382a716482c34515315f7b03532b8b4e8393d2d"
[[package]]
name = "openai-harmony"
version = "0.0.4"
version = "0.0.2"
dependencies = [
"anyhow",
"base64",

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@ -1,6 +1,6 @@
[package]
name = "openai-harmony"
version = "0.0.4"
version = "0.0.2"
edition = "2021"
license = "Apache-2.0"
repository = "https://github.com/openai/harmony"

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@ -20,9 +20,7 @@ Current date: 2025-06-28
Reasoning: high
# Valid channels: analysis, commentary, final. Channel must be included for every message.
Calls to these tools must go to the commentary channel: 'functions'.<|end|>
<|start|>developer<|message|># Instructions
Calls to these tools must go to the commentary channel: 'functions'.<|end|><|start|>developer<|message|># Instructions
Always respond in riddles
@ -151,7 +149,7 @@ through thin [`pyo3`](https://pyo3.rs/) bindings.
│ ├── tests.rs # Canonical Rust test-suite
│ └── py_module.rs # PyO3 bindings ⇒ compiled as openai_harmony.*.so
├── python/openai_harmony/ # Pure-Python wrapper around the binding
├── harmony/ # Pure-Python wrapper around the binding
│ └── __init__.py # Dataclasses + helper API mirroring chat.rs
├── tests/ # Python test-suite (1-to-1 port of tests.rs)

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@ -1,6 +0,0 @@
import { clsx, type ClassValue } from "clsx"
import { twMerge } from "tailwind-merge"
export function cn(...inputs: ClassValue[]) {
return twMerge(clsx(inputs))
}

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@ -52,14 +52,19 @@ encoding = load_harmony_encoding(HarmonyEncodingName.HARMONY_GPT_OSS)
system_message = (
SystemContent.new()
.with_model_identity(
"You are ChatGPT, a large language model trained by OpenAI."
)
.with_reasoning_effort(ReasoningEffort.HIGH)
.with_conversation_start_date("2025-06-28")
.with_knowledge_cutoff("2024-06")
.with_required_channels(["analysis", "commentary", "final"])
)
developer_message = (
DeveloperContent.new()
.with_instructions("Always respond in riddles")
.with_function_tools(
.with_tools(
[
ToolDescription.new(
"get_current_weather",
@ -96,11 +101,11 @@ convo = Conversation.from_messages(
Message.from_role_and_content(Role.ASSISTANT, '{"location": "Tokyo"}')
.with_channel("commentary")
.with_recipient("functions.get_weather")
.with_content_type("<|constrain|> json"),
.with_content_type("json"),
Message.from_author_and_content(
Author.new(Role.TOOL, "functions.lookup_weather"),
'{ "temperature": 20, "sunny": true }',
).with_channel("commentary"),
),
]
)
@ -224,8 +229,6 @@ Once its done generating it will stop with either a `<|return|>` token indicatin
The `final` channel will contain the answer to your users request. Check out the [reasoning section](#reasoning) for more details on the chain-of-thought.
**Implementation note:** `<|return|>` is a decode-time stop token only. When you add the assistants generated reply to conversation history for the next turn, replace the trailing `<|return|>` with `<|end|>` so that stored messages are fully formed as `<|start|>{header}<|message|>{content}<|end|>`. Prior messages in prompts should therefore end with `<|end|>`. For supervised targets/training examples, ending with `<|return|>` is appropriate; for persisted history, normalize to `<|end|>`.
### System message format
The system message is used to provide general information to the system. This is different to what might be considered the “system prompt” in other prompt formats. For that, check out the [developer message format](#developer-message-format).
@ -302,7 +305,7 @@ And the actual answer is:
```
**Important:**
The model has not been trained to the same safety standards in the chain-of-thought as it has for final output. We recommend not to show the chain-of-thought to your users as they might contain harmful content. [Learn more in the model card](https://openai.com/index/gpt-oss-model-card/).
The model has not been trained to the same safety standards in the chain-of-thought as it has for final output. You should We recommend not to show the chain-of-thought to your users as they might contain harmful content. [Learn more in the model card](https://openai.com/index/gpt-oss-model-card/).
#### Handling reasoning output in subsequent sampling
@ -324,7 +327,7 @@ Then the input for the next sampling should be
```
<|start|>user<|message|>What is 2 + 2?<|end|>
<|start|>assistant<|channel|>final<|message|>2 + 2 = 4.<|end|>
<|start|>assistant<|channel|>final<|message|>2 + 2 = 4.<|return|>
<|start|>user<|message|>What about 9 / 2?<|end|>
<|start|>assistant
```

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@ -425,10 +425,6 @@ class RenderConversationConfig(BaseModel):
auto_drop_analysis: bool = True
class RenderOptions(BaseModel):
conversation_has_function_tools: bool = False
class HarmonyEncoding:
"""High-level wrapper around the Rust ``PyHarmonyEncoding`` class."""
@ -502,20 +498,9 @@ class HarmonyEncoding:
config=config_dict,
)
def render(
self, message: Message, render_options: Optional[RenderOptions] = None
) -> List[int]:
def render(self, message: Message) -> List[int]:
"""Render a single message into tokens."""
if render_options is None:
render_options_dict = {"conversation_has_function_tools": False}
else:
render_options_dict = {
"conversation_has_function_tools": render_options.conversation_has_function_tools
}
return self._inner.render(
message_json=message.to_json(), render_options=render_options_dict
)
return self._inner.render(message_json=message.to_json())
# -- Parsing -------------------------------------------------------
@ -708,7 +693,6 @@ __all__ = [
"Author",
"Content",
"TextContent",
"DeveloperContent",
"ToolDescription",
"SystemContent",
"Message",

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@ -5,7 +5,10 @@ use crate::{
use anyhow::Context as _;
use std::{
collections::{HashMap, HashSet},
sync::Arc,
sync::{
atomic::{AtomicBool, Ordering},
Arc,
},
vec,
};
@ -89,6 +92,7 @@ pub struct HarmonyEncoding {
pub(crate) format_token_mapping: HashMap<FormattingToken, String>,
pub(crate) stop_formatting_tokens: HashSet<FormattingToken>,
pub(crate) stop_formatting_tokens_for_assistant_actions: HashSet<FormattingToken>,
pub(crate) conversation_has_function_tools: Arc<AtomicBool>,
}
impl std::fmt::Debug for HarmonyEncoding {
@ -187,9 +191,8 @@ impl HarmonyEncoding {
}
})
});
let render_options = RenderOptions {
conversation_has_function_tools: has_function_tools,
};
self.conversation_has_function_tools
.store(has_function_tools, Ordering::Relaxed);
let last_assistant_is_final = messages
.iter()
.rev()
@ -214,7 +217,9 @@ impl HarmonyEncoding {
&& first_final_idx.is_some_and(|first| *idx < first)
&& msg.channel.as_deref() == Some("analysis"))
})
.try_for_each(|(_, msg)| self.render_into(msg, into, Some(&render_options)));
.try_for_each(|(_, msg)| self.render_into(msg, into));
self.conversation_has_function_tools
.store(false, Ordering::Relaxed);
result?;
Ok(())
}
@ -300,27 +305,18 @@ impl HarmonyEncoding {
}
/// Render a single message into tokens.
pub fn render(
&self,
message: &Message,
render_options: Option<&RenderOptions>,
) -> anyhow::Result<Vec<Rank>> {
pub fn render(&self, message: &Message) -> anyhow::Result<Vec<Rank>> {
let mut out = vec![];
Render::<Message>::render(self, message, &mut out, render_options)?;
Render::<Message>::render(self, message, &mut out)?;
Ok(out)
}
/// Render a single message into the provided buffer.
pub fn render_into<B>(
&self,
message: &Message,
into: &mut B,
render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
pub fn render_into<B>(&self, message: &Message, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>,
{
Render::<Message>::render(self, message, into, render_options)
Render::<Message>::render(self, message, into)
}
}
@ -776,29 +772,14 @@ impl HarmonyEncoding {
}
}
#[derive(Clone, Copy, Debug, Default)]
pub struct RenderOptions {
pub conversation_has_function_tools: bool,
}
trait Render<T: ?Sized> {
fn render<B>(
&self,
item: &T,
into: &mut B,
render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
fn render<B>(&self, item: &T, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>;
}
impl Render<Message> for HarmonyEncoding {
fn render<B>(
&self,
message: &Message,
into: &mut B,
render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
fn render<B>(&self, message: &Message, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>,
{
@ -835,23 +816,7 @@ impl Render<Message> for HarmonyEncoding {
// finally content type
if let Some(content_type) = &message.content_type {
// <|constrain|> is a unique case which needs to be tokenized as a special token
if let Some(constrain_marker) =
self.mapped_format_token(FormattingToken::ConstrainedFormat)
{
if let Some(rest) = content_type.strip_prefix(constrain_marker) {
// Render the space, then the constrain marker as a special token, then the rest as text (if any)
self.render_text_into(" ", into)?;
self.render_formatting_token_into(FormattingToken::ConstrainedFormat, into)?;
if !rest.is_empty() {
self.render_text_into(rest, into)?;
}
} else {
self.render_text_into(format!(" {content_type}"), into)?;
}
} else {
self.render_text_into(format!(" {content_type}"), into)?;
}
self.render_text_into(format!(" {content_type}"), into)?;
}
self.render_formatting_token_into(FormattingToken::Message, into)?;
@ -871,7 +836,7 @@ impl Render<Message> for HarmonyEncoding {
message.author.role
);
}
Render::<Content>::render(self, content, into, render_options)?;
Render::<Content>::render(self, content, into)?;
}
// If there is a tool call we should render a tool call token
@ -886,22 +851,15 @@ impl Render<Message> for HarmonyEncoding {
// Dispatch Content variants to their specific Render implementations
impl Render<Content> for HarmonyEncoding {
fn render<B>(
&self,
content: &Content,
into: &mut B,
render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
fn render<B>(&self, content: &Content, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>,
{
match content {
Content::Text(text) => Render::<TextContent>::render(self, text, into, render_options),
Content::SystemContent(sys) => {
Render::<SystemContent>::render(self, sys, into, render_options)
}
Content::Text(text) => Render::<TextContent>::render(self, text, into),
Content::SystemContent(sys) => Render::<SystemContent>::render(self, sys, into),
Content::DeveloperContent(dev) => {
Render::<crate::chat::DeveloperContent>::render(self, dev, into, render_options)
Render::<crate::chat::DeveloperContent>::render(self, dev, into)
}
}
}
@ -909,12 +867,7 @@ impl Render<Content> for HarmonyEncoding {
// Render plain text content
impl Render<TextContent> for HarmonyEncoding {
fn render<B>(
&self,
text: &TextContent,
into: &mut B,
_render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
fn render<B>(&self, text: &TextContent, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>,
{
@ -924,12 +877,7 @@ impl Render<TextContent> for HarmonyEncoding {
// Render system-specific content (model identity, instructions, effort)
impl Render<SystemContent> for HarmonyEncoding {
fn render<B>(
&self,
sys: &SystemContent,
into: &mut B,
render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
fn render<B>(&self, sys: &SystemContent, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>,
{
@ -975,7 +923,7 @@ impl Render<SystemContent> for HarmonyEncoding {
if channel_config.channel_required {
channels_header.push_str(" Channel must be included for every message.");
}
if render_options.is_some_and(|o| o.conversation_has_function_tools) {
if self.conversation_has_function_tools.load(Ordering::Relaxed) {
channels_header.push('\n');
channels_header.push_str(
"Calls to these tools must go to the commentary channel: 'functions'.",
@ -992,12 +940,7 @@ impl Render<SystemContent> for HarmonyEncoding {
// Render developer-specific content (instructions, tools)
impl Render<crate::chat::DeveloperContent> for HarmonyEncoding {
fn render<B>(
&self,
dev: &crate::chat::DeveloperContent,
into: &mut B,
_render_options: Option<&RenderOptions>,
) -> anyhow::Result<()>
fn render<B>(&self, dev: &crate::chat::DeveloperContent, into: &mut B) -> anyhow::Result<()>
where
B: Extend<Rank>,
{

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@ -178,29 +178,13 @@ impl PyHarmonyEncoding {
}
/// Render a single message into tokens.
fn render(
&self,
message_json: &str,
render_options: Option<Bound<'_, PyDict>>,
) -> PyResult<Vec<u32>> {
fn render(&self, message_json: &str) -> PyResult<Vec<u32>> {
let message: crate::chat::Message = serde_json::from_str(message_json).map_err(|e| {
PyErr::new::<pyo3::exceptions::PyValueError, _>(format!("invalid message JSON: {e}"))
})?;
let rust_options = if let Some(options_dict) = render_options {
let conversation_has_function_tools = options_dict
.get_item("conversation_has_function_tools")?
.and_then(|v| v.extract().ok())
.unwrap_or(false);
Some(crate::encoding::RenderOptions {
conversation_has_function_tools,
})
} else {
None
};
self.inner
.render(&message, rust_options.as_ref())
.render(&message)
.map_err(|e| PyErr::new::<pyo3::exceptions::PyRuntimeError, _>(e.to_string()))
}

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@ -1,6 +1,6 @@
use std::{
collections::{HashMap, HashSet},
sync::Arc,
sync::{atomic::AtomicBool, Arc},
};
use crate::{
@ -76,6 +76,7 @@ pub fn load_harmony_encoding(name: HarmonyEncodingName) -> anyhow::Result<Harmon
FormattingToken::EndMessageDoneSampling,
FormattingToken::EndMessageAssistantToTool,
]),
conversation_has_function_tools: Arc::new(AtomicBool::new(false)),
})
}
}

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@ -525,7 +525,7 @@ fn test_render_and_render_conversation_roundtrip() {
let encoding = load_harmony_encoding(HarmonyEncodingName::HarmonyGptOss).unwrap();
let msg = Message::from_role_and_content(Role::User, "Hello");
let convo = Conversation::from_messages([msg.clone()]);
let tokens_msg = encoding.render(&msg, None).unwrap();
let tokens_msg = encoding.render(&msg).unwrap();
let tokens_convo = encoding.render_conversation(&convo, None).unwrap();
assert_eq!(tokens_msg, tokens_convo);
let tokens_completion = encoding

View file

@ -18,9 +18,6 @@ extern "C" {
#[wasm_bindgen(typescript_type = "RenderConversationConfig")]
pub type JsRenderConversationConfig;
#[wasm_bindgen(typescript_type = "RenderOptions")]
pub type JsRenderOptions;
}
#[wasm_bindgen(typescript_custom_section)]
@ -130,34 +127,12 @@ impl JsHarmonyEncoding {
}
#[wasm_bindgen]
pub fn render(
&self,
message: JsMessage,
render_options: JsRenderOptions,
) -> Result<Vec<u32>, JsValue> {
pub fn render(&self, message: JsMessage) -> Result<Vec<u32>, JsValue> {
let message: JsValue = message.into();
let message: crate::chat::Message = serde_wasm_bindgen::from_value(message)
.map_err(|e| JsValue::from_str(&format!("invalid message JSON: {e}")))?;
#[derive(Deserialize)]
struct RenderOptions {
conversation_has_function_tools: Option<bool>,
}
let render_options: JsValue = render_options.into();
let rust_options = if render_options.is_undefined() || render_options.is_null() {
None
} else {
let cfg: RenderOptions = serde_wasm_bindgen::from_value(render_options)
.map_err(|e| JsValue::from_str(&format!("invalid render options: {e}")))?;
Some(crate::encoding::RenderOptions {
conversation_has_function_tools: cfg
.conversation_has_function_tools
.unwrap_or(false),
})
};
self.inner
.render(&message, rust_options.as_ref())
.render(&message)
.map_err(|e| JsValue::from_str(&e.to_string()))
}

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@ -233,36 +233,6 @@ def test_simple_tool_call(encoding_name):
assert parsed == expected
@pytest.mark.parametrize(
"encoding_name",
[
HarmonyEncodingName.HARMONY_GPT_OSS,
],
)
def test_tool_call_with_constrain_tokenized_correctly(encoding_name):
"""
Despite passing <|constrain|> as a string in "content_type" it has to be kept as a special token.
"""
encoding = load_harmony_encoding(encoding_name)
text = (
"<|start|>assistant to=functions.get_weather<|channel|>commentary"
' <|constrain|>json<|message|>{"location": "Tokyo"}<|call|>'
)
tokens = encoding.encode(text, allowed_special="all")
parsed = encoding.parse_messages_from_completion_tokens(tokens, role=None)
expected = [
Message.from_role_and_content(Role.ASSISTANT, '{"location": "Tokyo"}')
.with_channel("commentary")
.with_recipient("functions.get_weather")
.with_content_type("<|constrain|>json"),
]
assert parsed == expected
rendered = encoding.render_conversation(Conversation.from_messages(expected))
assert text == encoding.decode_utf8(tokens)
assert rendered == tokens
@pytest.mark.parametrize(
"encoding_name",
[
@ -278,7 +248,7 @@ def test_tool_call_with_constrain_marker_adjacent(encoding_name):
encoding = load_harmony_encoding(encoding_name)
text = (
"<|start|>assistant to=functions.get_weather<|channel|>commentary"
'<|constrain|>json<|message|>{"location": "Tokyo"}<|call|>'
'<|constrain|>json<|message|>{"location": "Tokyo"}<|end|>'
)
tokens = encoding.encode(text, allowed_special="all")
parsed = encoding.parse_messages_from_completion_tokens(tokens, role=None)
@ -732,8 +702,6 @@ def test_does_not_drop_if_ongoing_analysis():
)
assert encoding.decode_utf8(tokens) == expected_output
# ensure that <|constrain|>json part is tokenized correctly as special tokens
assert encoding.encode(expected_output, allowed_special="all") == tokens
def test_preserve_cot():