use serde_json::{Value, json};
pub use sim_codec_chat::{encode_openai_request, encode_openai_response};
use sim_codec_json::json_number_to_u64;
use sim_kernel::{Error, Expr, Result};
use sim_value::access::{entry_field, entry_required_str_any, entry_required_sym_any};
pub fn encode_openai_responses_response(
expr: &Expr,
response_id: &str,
created_at_ms: u64,
) -> Result<Vec<u8>> {
let value = responses_response_json(expr, response_id, created_at_ms)?;
serde_json::to_vec(&value).map_err(|err| {
Error::Eval(format!(
"openai codec failed to encode responses response: {err}"
))
})
}
fn responses_response_json(expr: &Expr, response_id: &str, created_at_ms: u64) -> Result<Value> {
let Expr::Map(entries) = expr else {
return Err(Error::Eval(
"openai codec expects response transcript as a map".to_owned(),
));
};
let model = string_field(entries, "model")?;
let output_text = response_text(entries)?;
Ok(json!({
"id": response_id,
"object": "response",
"created_at": created_at_ms / 1000,
"status": "completed",
"model": model,
"output": [{
"type": "message",
"status": "completed",
"role": "assistant",
"content": [{
"type": "output_text",
"text": output_text,
"annotations": [],
}],
}],
"output_text": output_text,
"usage": response_usage(entries)?,
}))
}
fn response_text(entries: &[(Expr, Expr)]) -> Result<String> {
list_field(map_field(entries, "content")?)?
.iter()
.map(text_content)
.collect::<Result<Vec<_>>>()
.map(|parts| parts.join(""))
}
fn response_usage(entries: &[(Expr, Expr)]) -> Result<Value> {
let Some(usage) = entries.iter().find_map(|(field, value)| match field {
Expr::Symbol(symbol) if symbol.name.as_ref() == "usage" => Some(value),
_ => None,
}) else {
return Ok(Value::Null);
};
let Expr::Map(fields) = usage else {
return Err(Error::Eval(
"openai codec usage field must be a map".to_owned(),
));
};
let prompt = optional_u64_field(fields, "input-tokens")?;
let completion = optional_u64_field(fields, "output-tokens")?;
let total = optional_u64_field(fields, "total-tokens")?.or_else(|| {
prompt
.zip(completion)
.map(|(left, right)| left.saturating_add(right))
});
Ok(json!({
"prompt_tokens": prompt.unwrap_or(0),
"completion_tokens": completion.unwrap_or(0),
"total_tokens": total.unwrap_or(0),
}))
}
fn text_content(expr: &Expr) -> Result<String> {
let Expr::Map(entries) = expr else {
return Err(Error::Eval(
"openai codec content part must be a map".to_owned(),
));
};
match symbol_field(entries, "type")?.as_str() {
"text" => string_field(entries, "text"),
other => Err(Error::Eval(format!(
"openai codec does not support content part type {other}"
))),
}
}
fn optional_u64_field(entries: &[(Expr, Expr)], key: &str) -> Result<Option<u64>> {
let Some(value) = entries.iter().find_map(|(field, value)| match field {
Expr::Symbol(symbol) if symbol.name.as_ref() == key => Some(value),
_ => None,
}) else {
return Ok(None);
};
match value {
Expr::Number(number) => number
.canonical
.parse::<u64>()
.map(Some)
.map_err(|err| Error::Eval(format!("openai codec invalid {key}: {err}"))),
other => {
let json_number = match other {
Expr::String(text) => serde_json::from_str::<Value>(text).ok(),
_ => None,
};
json_number
.as_ref()
.and_then(json_number_to_u64)
.ok_or_else(|| Error::Eval(format!("openai codec field {key} must be a number")))
.map(Some)
}
}
}
fn symbol_field(entries: &[(Expr, Expr)], key: &str) -> Result<String> {
entry_required_sym_any(entries, key, "openai codec symbol field")
.map(|symbol| symbol.name.as_ref().to_owned())
}
fn string_field(entries: &[(Expr, Expr)], key: &str) -> Result<String> {
entry_required_str_any(entries, key, "openai codec string field").map(str::to_owned)
}
fn list_field(expr: &Expr) -> Result<&[Expr]> {
match expr {
Expr::List(items) => Ok(items),
_ => Err(Error::Eval("openai codec field must be a list".to_owned())),
}
}
fn map_field<'a>(entries: &'a [(Expr, Expr)], key: &str) -> Result<&'a Expr> {
entry_field(entries, key)
.ok_or_else(|| Error::Eval(format!("openai codec missing {key} field")))
}