mirror of
https://github.com/fawney19/Aether.git
synced 2026-10-12 20:19:51 +08:00
Merge branch 'main' of https://github.com/zhefox/Aether
This commit is contained in:
zhefox
@@ -29,6 +29,7 @@ struct OpenAIResponsesProviderToolState {
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call_id: String,
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name: String,
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arguments: String,
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emitted_arguments_len: usize,
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started_emitted: bool,
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}
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@@ -510,6 +511,74 @@ impl OpenAIResponsesProviderState {
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});
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}
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fn emit_ready_tool_call(
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&mut self,
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report_context: &Value,
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out: &mut Vec<CanonicalStreamFrame>,
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index: usize,
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) {
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let (id, model) = self.identity(report_context);
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let Some(state) = self.tool_calls.get_mut(&index) else {
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return;
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};
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if state.name.is_empty() {
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return;
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}
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if !state.started_emitted {
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out.push(CanonicalStreamFrame {
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id: id.clone(),
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model: model.clone(),
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event: CanonicalStreamEvent::ToolCallStart {
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index,
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call_id: if state.call_id.is_empty() {
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build_generated_tool_call_id(index)
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} else {
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state.call_id.clone()
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},
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name: state.name.clone(),
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},
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});
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state.started_emitted = true;
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}
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if state.emitted_arguments_len > state.arguments.len() {
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state.emitted_arguments_len = 0;
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}
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let pending = state
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.arguments
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.get(state.emitted_arguments_len..)
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.unwrap_or_default()
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.to_string();
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if pending.is_empty() {
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return;
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}
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state.emitted_arguments_len = state.arguments.len();
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out.push(CanonicalStreamFrame {
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id,
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model,
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event: CanonicalStreamEvent::ToolCallArgumentsDelta {
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index,
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arguments: pending,
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},
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});
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}
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fn merge_tool_call_arguments(state: &mut OpenAIResponsesProviderToolState, arguments: &str) {
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if arguments.is_empty() {
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return;
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}
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if arguments.starts_with(&state.arguments) {
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state
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.arguments
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.push_str(&arguments[state.arguments.len()..]);
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} else if state.arguments != arguments {
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if state.emitted_arguments_len == 0 {
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state.arguments = arguments.to_string();
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} else {
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state.arguments.push_str(arguments);
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}
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}
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}
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fn emit_tool_call_item(
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&mut self,
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report_context: &Value,
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@@ -527,7 +596,6 @@ impl OpenAIResponsesProviderState {
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.and_then(Value::as_str)
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.map(ToOwned::to_owned);
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let index = self.tool_index_for_key(key, output_index);
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let (id, model) = self.identity(report_context);
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let state = self.tool_calls.entry(index).or_default();
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state.call_id = item
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.get("call_id")
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@@ -540,50 +608,13 @@ impl OpenAIResponsesProviderState {
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.and_then(Value::as_str)
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.unwrap_or(state.name.as_str())
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.to_string();
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if !state.started_emitted {
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out.push(CanonicalStreamFrame {
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id: id.clone(),
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model: model.clone(),
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event: CanonicalStreamEvent::ToolCallStart {
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index,
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call_id: if state.call_id.is_empty() {
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build_generated_tool_call_id(index)
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} else {
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state.call_id.clone()
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},
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name: if state.name.is_empty() {
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"unknown".to_string()
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} else {
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state.name.clone()
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},
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},
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});
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state.started_emitted = true;
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}
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let completed_arguments = item
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.get("arguments")
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.and_then(Value::as_str)
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.unwrap_or_default()
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.to_string();
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let missing = if completed_arguments.starts_with(&state.arguments) {
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completed_arguments[state.arguments.len()..].to_string()
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} else if state.arguments == completed_arguments {
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String::new()
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} else {
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completed_arguments.clone()
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};
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if missing.is_empty() {
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return;
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}
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state.arguments.push_str(&missing);
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out.push(CanonicalStreamFrame {
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id,
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model,
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event: CanonicalStreamEvent::ToolCallArgumentsDelta {
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index,
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arguments: missing,
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},
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});
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Self::merge_tool_call_arguments(state, &completed_arguments);
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self.emit_ready_tool_call(report_context, out, index);
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}
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fn emit_missing_tool_result(
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@@ -978,44 +1009,22 @@ impl OpenAIResponsesProviderState {
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.and_then(Value::as_u64)
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.map(|value| value as usize);
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let index = self.tool_index_for_key(key, output_index);
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let (id, model) = self.identity(report_context);
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let state = self.tool_calls.entry(index).or_default();
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state.call_id = value
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.get("item_id")
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.or_else(|| value.get("call_id"))
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if let Some(call_id) = value
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.get("call_id")
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.or_else(|| value.get("id"))
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.and_then(Value::as_str)
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.unwrap_or(state.call_id.as_str())
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.to_string();
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if !state.started_emitted {
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out.push(CanonicalStreamFrame {
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id: id.clone(),
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model: model.clone(),
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event: CanonicalStreamEvent::ToolCallStart {
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index,
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call_id: if state.call_id.is_empty() {
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build_generated_tool_call_id(index)
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} else {
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state.call_id.clone()
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},
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name: if state.name.is_empty() {
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"unknown".to_string()
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} else {
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state.name.clone()
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},
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},
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});
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state.started_emitted = true;
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{
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state.call_id = call_id.to_string();
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} else if state.call_id.is_empty() {
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state.call_id = value
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.get("item_id")
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.and_then(Value::as_str)
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.unwrap_or_default()
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.to_string();
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}
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state.arguments.push_str(delta);
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out.push(CanonicalStreamFrame {
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id,
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model,
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event: CanonicalStreamEvent::ToolCallArgumentsDelta {
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index,
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arguments: delta.to_string(),
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},
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});
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self.emit_ready_tool_call(report_context, &mut out, index);
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}
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"response.function_call_arguments.done" => {
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let arguments = value
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@@ -1029,9 +1038,6 @@ impl OpenAIResponsesProviderState {
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.and_then(Value::as_str)
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})
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.unwrap_or_default();
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if arguments.is_empty() {
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return Ok(out);
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}
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self.ensure_started(report_context, &mut out);
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let key = value
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.get("item_id")
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@@ -1052,11 +1058,9 @@ impl OpenAIResponsesProviderState {
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.and_then(Value::as_u64)
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.map(|value| value as usize);
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let index = self.tool_index_for_key(key, output_index);
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let (id, model) = self.identity(report_context);
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let state = self.tool_calls.entry(index).or_default();
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state.call_id = value
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.get("item_id")
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.or_else(|| value.get("call_id"))
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.get("call_id")
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.or_else(|| value.get("id"))
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.and_then(Value::as_str)
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.or_else(|| {
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@@ -1066,46 +1070,23 @@ impl OpenAIResponsesProviderState {
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.and_then(|item| item.get("call_id").or_else(|| item.get("id")))
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.and_then(Value::as_str)
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})
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.or_else(|| value.get("item_id").and_then(Value::as_str))
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.unwrap_or(state.call_id.as_str())
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.to_string();
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if !state.started_emitted {
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out.push(CanonicalStreamFrame {
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id: id.clone(),
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model: model.clone(),
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event: CanonicalStreamEvent::ToolCallStart {
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index,
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call_id: if state.call_id.is_empty() {
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build_generated_tool_call_id(index)
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} else {
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state.call_id.clone()
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},
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name: if state.name.is_empty() {
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"unknown".to_string()
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} else {
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state.name.clone()
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},
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},
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});
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state.started_emitted = true;
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}
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let missing = if arguments.starts_with(&state.arguments) {
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arguments[state.arguments.len()..].to_string()
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} else if state.arguments == arguments {
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String::new()
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} else {
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arguments.to_string()
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};
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if !missing.is_empty() {
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state.arguments.push_str(&missing);
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out.push(CanonicalStreamFrame {
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id,
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model,
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event: CanonicalStreamEvent::ToolCallArgumentsDelta {
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index,
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arguments: missing,
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},
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});
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}
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state.name = value
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.get("name")
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.and_then(Value::as_str)
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.or_else(|| {
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value
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.get("item")
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.and_then(Value::as_object)
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.and_then(|item| item.get("name"))
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.and_then(Value::as_str)
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})
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.unwrap_or(state.name.as_str())
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.to_string();
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Self::merge_tool_call_arguments(state, arguments);
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self.emit_ready_tool_call(report_context, &mut out, index);
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}
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"response.function_call_output.delta" | "response.function_call_output.done" => {
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let tool_use_id = value
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@@ -2661,6 +2642,7 @@ fn openai_tool_result_content_from_value(value: Option<&Value>) -> String {
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#[cfg(test)]
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mod tests {
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use super::*;
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use crate::formats::claude::messages::stream::ClaudeClientEmitter;
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fn data_line(value: Value) -> Vec<u8> {
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format!("data: {}\n", value).into_bytes()
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@@ -3176,6 +3158,91 @@ mod tests {
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)));
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}
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#[test]
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fn openai_responses_provider_state_delays_arguments_until_tool_name_is_known() {
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let mut state = OpenAIResponsesProviderState::default();
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let report_context = json!({});
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let arguments = r#"{"file_path":"D:/projects/UIAutoTest/docs/prd/msr.md","offset":0,"limit":2000,"pages":""}"#;
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let mut frames = Vec::new();
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let delta_frames = state
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.push_line(
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&report_context,
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data_line(json!({
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"type": "response.function_call_arguments.delta",
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"response_id": "resp_read_123",
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"output_index": 0,
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"item_id": "fc_read_123",
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"delta": arguments,
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})),
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)
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.expect("arguments delta should parse");
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assert!(matches!(
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delta_frames.first().map(|frame| &frame.event),
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Some(CanonicalStreamEvent::Start)
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));
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assert!(!delta_frames.iter().any(|frame| matches!(
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frame.event,
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CanonicalStreamEvent::ToolCallStart { .. }
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| CanonicalStreamEvent::ToolCallArgumentsDelta { .. }
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)));
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frames.extend(delta_frames);
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frames.extend(
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state
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.push_line(
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&report_context,
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data_line(json!({
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"type": "response.function_call_arguments.done",
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"response_id": "resp_read_123",
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"output_index": 0,
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"item_id": "fc_read_123",
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"item": {
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"type": "function_call",
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"id": "fc_read_123",
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"call_id": "call_read_123",
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"name": "Read",
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"arguments": arguments,
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}
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})),
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)
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.expect("arguments done should parse"),
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);
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assert!(frames.iter().any(|frame| matches!(
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frame.event,
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CanonicalStreamEvent::ToolCallStart {
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ref call_id,
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ref name,
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..
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} if call_id == "call_read_123" && name == "Read"
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)));
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assert!(frames.iter().any(|frame| matches!(
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frame.event,
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CanonicalStreamEvent::ToolCallArgumentsDelta {
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ref arguments,
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..
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} if arguments.contains(r#""pages":"""#)
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)));
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let mut emitter = ClaudeClientEmitter::default();
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let mut bytes = Vec::new();
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for frame in frames {
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bytes.extend(emitter.emit(frame).expect("claude frame should encode"));
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}
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bytes.extend(
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emitter
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.finish()
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.expect("claude stream finish should encode"),
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);
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let sse = String::from_utf8(bytes).expect("claude sse should be utf8");
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assert!(sse.contains("\"name\":\"Read\""));
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assert!(sse.contains("\\\"limit\\\":2000"));
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assert!(!sse.contains("\\\"pages\\\":\\\"\\\""));
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}
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#[test]
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fn openai_responses_provider_state_parses_function_call_output_as_tool_result() {
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let mut state = OpenAIResponsesProviderState::default();
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Block a user