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https://github.com/fawney19/Aether.git
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fix: preserve claude tool results in openai chat conversion
Preserve all Claude tool_result blocks when emitting OpenAI Chat messages, including multimodal image/file content and is_error markers.
This commit is contained in:
stabey
@@ -157,7 +157,7 @@ fn request_context(mapped_model: &str, upstream_is_stream: bool) -> FormatContex
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#[cfg(test)]
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mod tests {
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use serde_json::json;
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use serde_json::{json, Value};
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use super::{
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convert_openai_chat_request_to_claude_request,
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@@ -215,4 +215,339 @@ mod tests {
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assert_eq!(converted["messages"][0]["role"], "user");
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assert_eq!(converted["messages"][0]["content"], "hello");
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}
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#[test]
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fn request_normalizer_preserves_multiple_claude_tool_results() {
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let body = json!({
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"model": "claude-sonnet",
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"messages": [
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{
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"role": "assistant",
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"content": [
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{
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"type": "tool_use",
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"id": "toolu_1",
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"name": "lookup",
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"input": {"query": "alpha"}
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},
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{
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"type": "tool_use",
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"id": "toolu_2",
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"name": "lookup",
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"input": {"query": "beta"}
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}
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]
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},
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{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_1",
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"content": "alpha result"
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},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_2",
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"content": [{"type": "text", "text": "beta result"}]
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}
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]
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}
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],
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"max_tokens": 128,
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});
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let converted =
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normalize_claude_request_to_openai_chat_request(&body).expect("openai chat request");
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let messages = converted["messages"].as_array().expect("messages");
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assert_eq!(messages.len(), 3);
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assert_eq!(messages[0]["role"], "assistant");
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assert_eq!(messages[0]["tool_calls"].as_array().unwrap().len(), 2);
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assert_eq!(messages[0]["tool_calls"][0]["id"], "toolu_1");
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assert_eq!(messages[0]["tool_calls"][1]["id"], "toolu_2");
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assert_eq!(messages[1]["role"], "tool");
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assert_eq!(messages[1]["tool_call_id"], "toolu_1");
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assert_eq!(messages[1]["content"], "alpha result");
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assert_eq!(messages[2]["role"], "tool");
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assert_eq!(messages[2]["tool_call_id"], "toolu_2");
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assert_eq!(messages[2]["content"], "beta result");
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}
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#[test]
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fn request_normalizer_preserves_claude_tool_result_order_around_text() {
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let body = json!({
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"model": "claude-sonnet",
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"messages": [{
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"role": "user",
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"content": [
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{"type": "text", "text": "before"},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_1",
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"content": "first"
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},
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{"type": "text", "text": "between"},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_2",
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"content": "second"
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}
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]
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}],
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"max_tokens": 128,
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});
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let converted =
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normalize_claude_request_to_openai_chat_request(&body).expect("openai chat request");
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let messages = converted["messages"].as_array().expect("messages");
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assert_eq!(messages.len(), 4);
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assert_eq!(messages[0]["role"], "user");
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assert_eq!(messages[0]["content"], "before");
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assert_eq!(messages[1]["role"], "tool");
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assert_eq!(messages[1]["tool_call_id"], "toolu_1");
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assert_eq!(messages[1]["content"], "first");
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assert_eq!(messages[2]["role"], "user");
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assert_eq!(messages[2]["content"], "between");
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assert_eq!(messages[3]["role"], "tool");
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assert_eq!(messages[3]["tool_call_id"], "toolu_2");
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assert_eq!(messages[3]["content"], "second");
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}
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#[test]
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fn request_normalizer_marks_claude_error_tool_result_string_and_object_content() {
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let object_result = json!({"code": "ENOENT", "message": "missing"});
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let body = json!({
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"model": "claude-sonnet",
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"messages": [{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_error_string",
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"content": "lookup failed",
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"is_error": true
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},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_error_empty",
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"content": "",
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"is_error": true
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},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_error_object",
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"content": object_result,
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"is_error": true
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},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_ok",
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"content": "still ok"
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}
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]
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}],
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"max_tokens": 128,
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});
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let converted =
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normalize_claude_request_to_openai_chat_request(&body).expect("openai chat request");
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let messages = converted["messages"].as_array().expect("messages");
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assert_eq!(messages.len(), 4);
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assert_eq!(messages[0]["role"], "tool");
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assert_eq!(messages[0]["tool_call_id"], "toolu_error_string");
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assert_eq!(messages[0]["content"], "[tool error]\nlookup failed");
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assert_eq!(messages[1]["role"], "tool");
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assert_eq!(messages[1]["tool_call_id"], "toolu_error_empty");
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assert_eq!(messages[1]["content"], "[tool error]");
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assert_eq!(messages[2]["role"], "tool");
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assert_eq!(messages[2]["tool_call_id"], "toolu_error_object");
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let object_content = messages[2]["content"].as_str().expect("object content");
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let serialized_object = object_content
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.strip_prefix("[tool error]\n")
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.expect("error prefix");
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assert_eq!(
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serde_json::from_str::<Value>(serialized_object).expect("serialized object"),
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object_result
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);
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assert_eq!(messages[3]["role"], "tool");
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assert_eq!(messages[3]["tool_call_id"], "toolu_ok");
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assert_eq!(messages[3]["content"], "still ok");
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}
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#[test]
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fn request_normalizer_marks_claude_error_tool_result_multipart_image_content() {
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let body = json!({
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"model": "claude-sonnet",
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"messages": [{
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"role": "user",
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"content": [{
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"type": "tool_result",
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"tool_use_id": "toolu_error_image",
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"content": [
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{"type": "text", "text": "preview"},
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{
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": "image/png",
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"data": "aW1hZ2U="
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}
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}
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],
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"is_error": true
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}]
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}],
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"max_tokens": 128,
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});
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let converted =
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normalize_claude_request_to_openai_chat_request(&body).expect("openai chat request");
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let messages = converted["messages"].as_array().expect("messages");
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assert_eq!(messages.len(), 1);
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assert_eq!(messages[0]["role"], "tool");
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assert_eq!(messages[0]["tool_call_id"], "toolu_error_image");
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let content = messages[0]["content"]
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.as_array()
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.expect("multipart error content");
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assert_eq!(
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content.as_slice(),
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&[
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json!({"type": "text", "text": "[tool error]"}),
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json!({"type": "text", "text": "preview"}),
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json!({
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"type": "image_url",
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"image_url": {"url": "data:image/png;base64,aW1hZ2U="}
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}),
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]
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);
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}
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#[test]
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fn request_normalizer_preserves_legal_openai_tool_content_for_claude_variants() {
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let anthropic_blocks = json!([
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{"type": "text", "text": "preview"},
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{
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": "image/jpeg",
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"data": "aGVsbG8="
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}
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},
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{
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"type": "image",
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"source": {
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"type": "url",
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"url": "https://example.com/image.jpg"
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}
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},
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{
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"type": "document",
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"source": {
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"type": "base64",
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"media_type": "application/pdf",
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"data": "JVBERi0x"
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}
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},
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{
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"type": "document",
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"source": {
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"type": "url",
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"url": "https://example.com/report.pdf"
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}
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},
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{
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"type": "document",
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"source": {
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"type": "text",
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"media_type": "text/plain",
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"data": "document body"
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}
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}
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]);
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let object_result = json!({"answer": 42, "ok": true});
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let body = json!({
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"model": "claude-sonnet",
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"messages": [{
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"role": "user",
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"content": [
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{
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"type": "tool_result",
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"tool_use_id": "toolu_object",
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"content": object_result
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},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_text_blocks",
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"content": [
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{"type": "text", "text": "line one"},
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{"type": "text", "text": "line two"}
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]
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},
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{
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"type": "tool_result",
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"tool_use_id": "toolu_anthropic_blocks",
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"content": anthropic_blocks
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}
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]
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}],
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"max_tokens": 128,
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});
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let converted =
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normalize_claude_request_to_openai_chat_request(&body).expect("openai chat request");
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let messages = converted["messages"].as_array().expect("messages");
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assert_eq!(messages.len(), 3);
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assert_eq!(messages[0]["role"], "tool");
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assert_eq!(messages[0]["tool_call_id"], "toolu_object");
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let object_content = messages[0]["content"].as_str().expect("object content");
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assert_eq!(
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serde_json::from_str::<Value>(object_content).expect("serialized object"),
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object_result
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);
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assert_eq!(messages[1]["role"], "tool");
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assert_eq!(messages[1]["tool_call_id"], "toolu_text_blocks");
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assert_eq!(messages[1]["content"], "line one\n\nline two");
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assert_eq!(messages[2]["role"], "tool");
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assert_eq!(messages[2]["tool_call_id"], "toolu_anthropic_blocks");
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let block_content = messages[2]["content"]
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.as_array()
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.expect("multipart anthropic block content");
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assert_eq!(
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block_content.as_slice(),
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&[
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json!({"type": "text", "text": "preview"}),
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json!({
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"type": "image_url",
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"image_url": {"url": "data:image/jpeg;base64,aGVsbG8="}
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}),
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json!({
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"type": "image_url",
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"image_url": {"url": "https://example.com/image.jpg"}
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}),
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json!({
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"type": "file",
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"file": {"file_data": "data:application/pdf;base64,JVBERi0x"}
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}),
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json!({"type": "text", "text": "[File: https://example.com/report.pdf]"}),
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json!({
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"type": "text",
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"text": "[Claude tool_result document content omitted: text/plain]"
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}),
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]
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);
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let block_content_json = Value::Array(block_content.clone()).to_string();
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assert!(!block_content_json.contains("\"source\""));
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assert!(!block_content_json.contains("document body"));
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}
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}
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@@ -3,7 +3,7 @@ use serde_json::{json, Value};
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use crate::{
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formats::context::FormatContext,
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protocol::canonical::{
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canonical_extension_object_mut, canonical_message_to_openai_chat,
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canonical_extension_object_mut, canonical_message_to_openai_chat_messages,
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canonical_response_format_to_openai, canonical_tool_choice_to_openai,
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canonical_tool_to_openai, namespace_extension_object, openai_content_text,
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openai_extensions, openai_generation_config, openai_message_content_blocks,
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@@ -148,7 +148,7 @@ pub fn to_raw(canonical: &CanonicalRequest) -> Value {
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}
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}
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for message in &canonical.messages {
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messages.push(canonical_message_to_openai_chat(message));
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messages.extend(canonical_message_to_openai_chat_messages(message));
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}
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output.insert("messages".to_string(), Value::Array(messages));
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