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Aether/crates/aether-ai-formats/src/formats/openai/responses/request.rs
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use serde_json::{json, Map, Value};
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use crate::{
formats::context::FormatContext,
formats::openai::shared::map_thinking_budget_to_openai_reasoning_effort,
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protocol::canonical::{
canonical_response_format_to_openai, canonicalize_tool_arguments, media_data_or_url,
namespace_extension_object, openai_content_text, openai_extensions,
openai_response_format_to_canonical, openai_responses_extension,
openai_responses_generation_config, openai_responses_input_to_canonical_messages,
openai_responses_tool_choice_to_canonical, openai_responses_tools_to_canonical,
CanonicalContentBlock, CanonicalInstruction, CanonicalRequest, CanonicalRole,
CanonicalThinkingConfig, CanonicalToolChoice, CanonicalToolDefinition,
OPENAI_RESPONSES_EXTENSION_NAMESPACE, OPENAI_RESPONSES_LEGACY_EXTENSION_NAMESPACE,
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},
};
pub fn from(body: &Value, _ctx: &FormatContext) -> Option<CanonicalRequest> {
from_raw(body)
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}
pub fn to(request: &CanonicalRequest, ctx: &FormatContext) -> Option<Value> {
to_raw(
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request,
ctx.mapped_model_or(request.model.as_str()),
ctx.upstream_is_stream,
false,
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)
}
pub fn to_compact(request: &CanonicalRequest, ctx: &FormatContext) -> Option<Value> {
to_raw(
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request,
ctx.mapped_model_or(request.model.as_str()),
false,
true,
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)
}
pub fn from_raw(body_json: &Value) -> Option<CanonicalRequest> {
let request = body_json.as_object()?;
let mut canonical = CanonicalRequest {
model: request
.get("model")
.and_then(Value::as_str)
.unwrap_or_default()
.to_string(),
..CanonicalRequest::default()
};
if let Some(instructions) = request.get("instructions") {
let text = openai_content_text(Some(instructions));
if !text.trim().is_empty() {
canonical.system = Some(text.clone());
canonical.instructions.push(CanonicalInstruction {
role: CanonicalRole::System,
text,
extensions: std::collections::BTreeMap::new(),
});
}
}
canonical.messages = openai_responses_input_to_canonical_messages(request.get("input"))?;
canonical.generation = openai_responses_generation_config(request);
canonical.tools = openai_responses_tools_to_canonical(request.get("tools"))?;
canonical.tool_choice = openai_responses_tool_choice_to_canonical(request.get("tool_choice"));
canonical.parallel_tool_calls = request.get("parallel_tool_calls").and_then(Value::as_bool);
canonical.metadata = request.get("metadata").cloned();
canonical.response_format = request
.get("text")
.and_then(Value::as_object)
.and_then(|text| text.get("format"))
.and_then(|format| openai_response_format_to_canonical(Some(format)));
if let Some(reasoning) = request.get("reasoning").and_then(Value::as_object) {
let mut extensions = std::collections::BTreeMap::new();
extensions.insert(
OPENAI_RESPONSES_EXTENSION_NAMESPACE.to_string(),
Value::Object(reasoning.clone()),
);
canonical.thinking = Some(CanonicalThinkingConfig {
enabled: true,
budget_tokens: reasoning.get("budget_tokens").and_then(Value::as_u64),
extensions,
});
}
canonical.extensions = openai_extensions(
request,
&[
"model",
"instructions",
"input",
"max_output_tokens",
"temperature",
"top_p",
"metadata",
"tools",
"tool_choice",
"parallel_tool_calls",
"text",
"reasoning",
],
);
if let Some(raw) = canonical.extensions.remove("openai") {
canonical
.extensions
.insert(OPENAI_RESPONSES_EXTENSION_NAMESPACE.to_string(), raw);
}
if let Some(verbosity) = request
.get("text")
.and_then(Value::as_object)
.and_then(|text| text.get("verbosity"))
.cloned()
{
let entry = canonical
.extensions
.entry(OPENAI_RESPONSES_EXTENSION_NAMESPACE.to_string())
.or_insert_with(|| Value::Object(serde_json::Map::new()));
if let Some(object) = entry.as_object_mut() {
object.insert("verbosity".to_string(), verbosity);
}
}
Some(canonical)
}
pub fn to_raw(
canonical: &CanonicalRequest,
mapped_model: &str,
upstream_is_stream: bool,
compact: bool,
) -> Option<Value> {
let mut output = Map::new();
output.insert("model".to_string(), Value::String(mapped_model.to_string()));
if let Some(instructions) = canonical_instructions_to_responses(canonical) {
output.insert("instructions".to_string(), instructions);
}
output.insert(
"input".to_string(),
Value::Array(canonical_messages_to_responses_input(canonical)?),
);
if upstream_is_stream && !compact {
output.insert("stream".to_string(), Value::Bool(true));
}
if let Some(max_tokens) = canonical.generation.max_tokens {
output.insert("max_output_tokens".to_string(), Value::from(max_tokens));
}
insert_number(&mut output, "temperature", canonical.generation.temperature);
insert_number(&mut output, "top_p", canonical.generation.top_p);
if let Some(top_logprobs) = canonical.generation.top_logprobs {
output.insert("top_logprobs".to_string(), Value::from(top_logprobs));
}
if let Some(value) = canonical.parallel_tool_calls {
output.insert("parallel_tool_calls".to_string(), Value::Bool(value));
}
if let Some(metadata) = canonical.metadata.clone() {
output.insert("metadata".to_string(), metadata);
}
if let Some(text_config) = canonical_text_config_to_responses(canonical) {
output.insert("text".to_string(), text_config);
}
if !canonical.tools.is_empty() {
output.insert(
"tools".to_string(),
Value::Array(canonical_tools_to_responses(canonical)),
);
}
if let Some(tool_choice) = canonical.tool_choice.as_ref() {
output.insert(
"tool_choice".to_string(),
canonical_tool_choice_to_responses(tool_choice),
);
}
if let Some(reasoning) = canonical
.thinking
.as_ref()
.and_then(reasoning_config_to_responses)
{
output.insert("reasoning".to_string(), reasoning);
}
output.extend(namespace_extension_object(
&canonical.extensions,
OPENAI_RESPONSES_EXTENSION_NAMESPACE,
&output,
));
output.extend(namespace_extension_object(
&canonical.extensions,
OPENAI_RESPONSES_LEGACY_EXTENSION_NAMESPACE,
&output,
));
if compact {
output.remove("stream");
}
output.remove("verbosity");
Some(Value::Object(output))
}
fn canonical_instructions_to_responses(canonical: &CanonicalRequest) -> Option<Value> {
let text = canonical
.instructions
.iter()
.map(|instruction| instruction.text.as_str())
.filter(|text| !text.trim().is_empty())
.collect::<Vec<_>>()
.join("\n\n");
if !text.trim().is_empty() {
return Some(Value::String(text));
}
canonical
.system
.as_ref()
.filter(|value| !value.trim().is_empty())
.cloned()
.map(Value::String)
}
fn canonical_messages_to_responses_input(canonical: &CanonicalRequest) -> Option<Vec<Value>> {
let mut input = Vec::new();
for message in &canonical.messages {
let role = match message.role {
CanonicalRole::Assistant => "assistant",
CanonicalRole::Tool | CanonicalRole::User | CanonicalRole::Unknown => "user",
CanonicalRole::System | CanonicalRole::Developer => continue,
};
let mut content = Vec::new();
for block in &message.content {
match block {
CanonicalContentBlock::ToolUse {
id,
name,
input: arguments,
..
} => {
flush_responses_message(&mut input, role, &mut content);
input.push(json!({
"type": "function_call",
"call_id": id,
"name": name,
"arguments": canonicalize_tool_arguments(arguments),
}));
}
CanonicalContentBlock::ToolResult {
tool_use_id,
output,
content_text,
..
} => {
flush_responses_message(&mut input, role, &mut content);
input.push(json!({
"type": "function_call_output",
"call_id": tool_use_id,
"output": responses_tool_result_output(output.as_ref(), content_text.as_deref()),
}));
}
CanonicalContentBlock::Thinking { .. } => {}
other => {
if let Some(part) = canonical_block_to_responses_input_part(other, role) {
content.push(part);
}
}
}
}
flush_responses_message(&mut input, role, &mut content);
}
Some(input)
}
fn flush_responses_message(input: &mut Vec<Value>, role: &str, content: &mut Vec<Value>) {
if content.is_empty() {
return;
}
input.push(json!({
"type": "message",
"role": role,
"content": std::mem::take(content),
}));
}
fn canonical_block_to_responses_input_part(
block: &CanonicalContentBlock,
role: &str,
) -> Option<Value> {
match block {
CanonicalContentBlock::Text { text, .. } => {
if text.is_empty() {
return None;
}
Some(json!({
"type": if role == "assistant" { "output_text" } else { "input_text" },
"text": text,
}))
}
CanonicalContentBlock::Image {
data,
url,
media_type,
detail,
..
} => {
let mut item = Map::new();
item.insert(
"type".to_string(),
Value::String(if role == "assistant" {
"output_image".to_string()
} else {
"input_image".to_string()
}),
);
item.insert(
"image_url".to_string(),
Value::String(media_data_or_url(media_type, data, url)),
);
if let Some(detail) = detail {
item.insert("detail".to_string(), Value::String(detail.clone()));
}
Some(Value::Object(item))
}
CanonicalContentBlock::File {
data,
file_id,
file_url,
media_type,
filename,
..
} => {
let mut item = Map::new();
item.insert("type".to_string(), Value::String("input_file".to_string()));
if let Some(value) = file_id {
item.insert("file_id".to_string(), Value::String(value.clone()));
}
if data.is_some() || file_url.is_some() {
item.insert(
"file_data".to_string(),
Value::String(media_data_or_url(media_type, data, file_url)),
);
}
if let Some(value) = filename {
item.insert("filename".to_string(), Value::String(value.clone()));
}
(item.len() > 1).then_some(Value::Object(item))
}
CanonicalContentBlock::Audio { data, format, .. } => Some(json!({
"type": "input_audio",
"input_audio": {
"data": data.clone().unwrap_or_default(),
"format": format.clone().unwrap_or_else(|| "mp3".to_string()),
}
})),
CanonicalContentBlock::Unknown {
raw_type, payload, ..
} if raw_type == "refusal" => payload
.get("refusal")
.and_then(Value::as_str)
.filter(|text| !text.trim().is_empty())
.map(|text| json!({ "type": "refusal", "refusal": text })),
CanonicalContentBlock::Thinking { .. }
| CanonicalContentBlock::ToolUse { .. }
| CanonicalContentBlock::ToolResult { .. }
| CanonicalContentBlock::Unknown { .. } => None,
}
}
fn canonical_tools_to_responses(canonical: &CanonicalRequest) -> Vec<Value> {
let mut tools = canonical
.tools
.iter()
.map(canonical_tool_to_responses)
.collect::<Vec<_>>();
if let Some(extra_tools) = canonical
.extensions
.get(OPENAI_RESPONSES_EXTENSION_NAMESPACE)
.or_else(|| {
canonical
.extensions
.get(OPENAI_RESPONSES_LEGACY_EXTENSION_NAMESPACE)
})
.and_then(Value::as_object)
.and_then(|value| value.get("tools"))
.and_then(Value::as_array)
{
tools.extend(extra_tools.iter().cloned());
}
tools
}
fn reasoning_config_to_responses(thinking: &CanonicalThinkingConfig) -> Option<Value> {
openai_responses_extension(&thinking.extensions)
.cloned()
.or_else(|| {
thinking
.extensions
.get(OPENAI_RESPONSES_LEGACY_EXTENSION_NAMESPACE)
.cloned()
})
.or_else(|| {
thinking
.extensions
.get("openai")
.and_then(|value| value.get("reasoning_effort"))
.and_then(Value::as_str)
.map(|effort| {
json!({
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"effort": openai_responses_reasoning_effort(effort),
})
})
})
.or_else(|| {
thinking.budget_tokens.map(|budget_tokens| {
json!({
"effort": map_thinking_budget_to_openai_reasoning_effort(budget_tokens),
})
})
})
}
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fn openai_responses_reasoning_effort(effort: &str) -> &str {
match effort.trim().to_ascii_lowercase().as_str() {
"xhigh" | "max" => "xhigh",
"low" => "low",
"medium" => "medium",
"high" => "high",
_ => effort,
}
}
fn canonical_text_config_to_responses(canonical: &CanonicalRequest) -> Option<Value> {
let mut text = Map::new();
if let Some(response_format) = &canonical.response_format {
text.insert(
"format".to_string(),
canonical_response_format_to_openai(response_format),
);
}
if let Some(verbosity) = canonical
.extensions
.get(OPENAI_RESPONSES_EXTENSION_NAMESPACE)
.or_else(|| {
canonical
.extensions
.get(OPENAI_RESPONSES_LEGACY_EXTENSION_NAMESPACE)
})
.and_then(Value::as_object)
.and_then(|value| value.get("verbosity"))
.cloned()
{
text.insert("verbosity".to_string(), verbosity);
}
(!text.is_empty()).then_some(Value::Object(text))
}
fn canonical_tool_to_responses(tool: &CanonicalToolDefinition) -> Value {
if let Some(raw) = tool
.extensions
.get(OPENAI_RESPONSES_EXTENSION_NAMESPACE)
.or_else(|| {
tool.extensions
.get(OPENAI_RESPONSES_LEGACY_EXTENSION_NAMESPACE)
})
.filter(|value| {
value
.get("type")
.and_then(Value::as_str)
.is_some_and(|tool_type| {
tool_type == "custom" || tool_type.starts_with("web_search")
})
})
{
return raw.clone();
}
let mut out = Map::new();
out.insert("type".to_string(), Value::String("function".to_string()));
out.insert("name".to_string(), Value::String(tool.name.clone()));
if let Some(description) = &tool.description {
out.insert(
"description".to_string(),
Value::String(description.clone()),
);
}
if let Some(parameters) = &tool.parameters {
out.insert("parameters".to_string(), parameters.clone());
}
out.extend(namespace_extension_object(
&tool.extensions,
OPENAI_RESPONSES_EXTENSION_NAMESPACE,
&out,
));
Value::Object(out)
}
fn canonical_tool_choice_to_responses(choice: &CanonicalToolChoice) -> Value {
match choice {
CanonicalToolChoice::Auto => Value::String("auto".to_string()),
CanonicalToolChoice::None => Value::String("none".to_string()),
CanonicalToolChoice::Required => Value::String("required".to_string()),
CanonicalToolChoice::Tool { name } => json!({
"type": "function",
"name": name,
}),
}
}
fn responses_tool_result_output(output: Option<&Value>, content_text: Option<&str>) -> Value {
match output {
Some(Value::String(text)) => Value::String(text.clone()),
Some(value) => serde_json::to_string(value)
.map(Value::String)
.unwrap_or_else(|_| Value::String(String::new())),
None => Value::String(content_text.unwrap_or_default().to_string()),
}
}
fn insert_number(output: &mut Map<String, Value>, key: &str, value: Option<f64>) {
if let Some(value) = value.and_then(serde_json::Number::from_f64) {
output.insert(key.to_string(), Value::Number(value));
}
}