fix: model narration included in history and between tool calls to prevent repetition

src/client/bedrock.rs

@@ -397,6 +397,11 @@ fn build_chat_completions_body(data: ChatCompletionsData, model: &Model) -> Resu
                         }))
                     }
                     for tool_result in tool_results {
+                        if let Some(round_text) = &tool_result.text {
+                            assistant_parts.push(json!({
+                                "text": round_text,
+                            }))
+                        }
                         assistant_parts.push(json!({
                             "toolUse": {
                                 "toolUseId": tool_result.call.id,

src/client/claude.rs

@@ -320,6 +320,12 @@ pub fn claude_build_chat_completions_body(
                         }))
                     }
                     for tool_result in tool_results {
+                        if let Some(round_text) = &tool_result.text {
+                            assistant_parts.push(json!({
+                                "type": "text",
+                                "text": round_text,
+                            }))
+                        }
                         assistant_parts.push(json!({
                             "type": "tool_use",
                             "id": tool_result.call.id,

src/client/message.rs

@@ -118,6 +118,9 @@ impl MessageContent {
                     lines.push(text.clone())
                 }
                 for tool_result in tool_results {
+                    if let Some(round_text) = &tool_result.text {
+                        lines.push(round_text.clone())
+                    }
                     let mut parts = vec!["Call".to_string()];
                     if let Some((agent_name, functions)) = agent_info
                         && functions.contains(&tool_result.call.name)
@@ -201,9 +204,13 @@ impl MessageContentToolCalls {
         }
     }
 
-    pub fn merge(&mut self, tool_results: Vec<ToolResult>, _text: String) {
+    pub fn merge(&mut self, mut tool_results: Vec<ToolResult>, text: String) {
+        if !text.is_empty()
+            && let Some(first) = tool_results.first_mut()
+        {
+            first.text = Some(text);
+        }
         self.tool_results.extend(tool_results);
-        self.text.clear();
         self.sequence = true;
     }
 }

src/client/openai.rs

@@ -370,7 +370,7 @@ pub fn openai_build_chat_completions_body(data: ChatCompletionsData, model: &Mod
             match content {
                 MessageContent::ToolCalls(MessageContentToolCalls {
                     tool_results,
-                    text: _,
+                    text,
                     sequence,
                 }) => {
                     if !sequence {
@@ -387,9 +387,12 @@ pub fn openai_build_chat_completions_body(data: ChatCompletionsData, model: &Mod
                                 })
                             })
                             .collect();
-                        let mut messages = vec![
-                            json!({ "role": MessageRole::Assistant, "tool_calls": tool_calls }),
-                        ];
+                        let mut assistant_message =
+                            json!({ "role": MessageRole::Assistant, "tool_calls": tool_calls });
+                        if !text.is_empty() {
+                            assistant_message["content"] = strip_think_tag(&text).into();
+                        }
+                        let mut messages = vec![assistant_message];
                         for tool_result in tool_results {
                             messages.push(json!({
                                 "role": "tool",
@@ -399,9 +402,13 @@ pub fn openai_build_chat_completions_body(data: ChatCompletionsData, model: &Mod
                         }
                         messages
                     } else {
-                        tool_results.into_iter().flat_map(|tool_result| {
-                            vec![
-                                json!({
+                        tool_results.into_iter().enumerate().flat_map(|(index, tool_result)| {
+                            let round_text = if index == 0 && !text.is_empty() {
+                                Some(text.clone())
+                            } else {
+                                tool_result.text.clone()
+                            };
+                            let mut assistant_message = json!({
                                 "role": MessageRole::Assistant,
                                 "tool_calls": [
                                     {
@@ -413,7 +420,12 @@ pub fn openai_build_chat_completions_body(data: ChatCompletionsData, model: &Mod
                                         },
                                     }
                                 ]
-                                }),
+                            });
+                            if let Some(round_text) = round_text {
+                                assistant_message["content"] = strip_think_tag(&round_text).into();
+                            }
+                            vec![
+                                assistant_message,
                                 json!({
                                     "role": "tool",
                                     "content": tool_result.output.to_string(),
@@ -552,24 +564,36 @@ pub fn openai_build_responses_body(data: ChatCompletionsData, model: &Model) ->
             match content {
                 MessageContent::ToolCalls(MessageContentToolCalls {
                     tool_results,
-                    text: _,
+                    text,
                     sequence: _,
                 }) => tool_results
                     .into_iter()
-                    .flat_map(|tool_result| {
-                        vec![
-                            json!({
+                    .enumerate()
+                    .flat_map(|(index, tool_result)| {
+                        let round_text = if index == 0 && !text.is_empty() {
+                            Some(text.clone())
+                        } else {
+                            tool_result.text.clone()
+                        };
+                        let mut items = vec![];
+                        if let Some(round_text) = round_text {
+                            items.push(json!({
+                                "role": MessageRole::Assistant,
+                                "content": strip_think_tag(&round_text),
+                            }));
+                        }
+                        items.push(json!({
                             "type": "function_call",
                             "call_id": tool_result.call.id,
                             "name": tool_result.call.name,
                             "arguments": tool_result.call.arguments.to_string(),
-                            }),
-                            json!({
+                        }));
+                        items.push(json!({
                             "type": "function_call_output",
                             "call_id": tool_result.call.id,
                             "output": tool_result.output.to_string(),
-                            }),
-                        ]
+                        }));
+                        items
                     })
                     .collect(),
                 MessageContent::Text(text) if role.is_assistant() && i != messages_len - 1 => {

src/client/vertexai.rs

@@ -372,8 +372,15 @@ pub fn gemini_build_chat_completions_body(
                             .collect();
                         vec![json!({ "role": role, "parts": parts })]
                     },
-                    MessageContent::ToolCalls(MessageContentToolCalls { tool_results, .. }) => {
-                        let model_parts: Vec<Value> = tool_results.iter().map(|tool_result| {
+                    MessageContent::ToolCalls(MessageContentToolCalls { tool_results, text, .. }) => {
+                        let mut model_parts: Vec<Value> = vec![];
+                        if !text.is_empty() {
+                            model_parts.push(json!({ "text": text }));
+                        }
+                        for tool_result in tool_results.iter() {
+                            if let Some(round_text) = &tool_result.text {
+                                model_parts.push(json!({ "text": round_text }));
+                            }
                             let mut part = json!({
                                 "functionCall": {
                                     "name": tool_result.call.name,
@@ -383,8 +390,8 @@ pub fn gemini_build_chat_completions_body(
                             if let Some(sig) = &tool_result.call.thought_signature {
                                 part["thoughtSignature"] = json!(sig);
                             }
-                            part
-                        }).collect();
+                            model_parts.push(part);
+                        }
                         let function_parts: Vec<Value> = tool_results.into_iter().map(|tool_result| {
                             json!({
                                 "functionResponse": {

src/function/mod.rs

@@ -203,11 +203,17 @@ fn normalize_tool_result(result: Value) -> Value {
 pub struct ToolResult {
     pub call: ToolCall,
     pub output: Value,
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub text: Option<String>,
 }
 
 impl ToolResult {
     pub fn new(call: ToolCall, output: Value) -> Self {
-        Self { call, output }
+        Self {
+            call,
+            output,
+            text: None,
+        }
     }
 }