feat: 增强OpenAIProvider以支持工具调用参数的JSON格式，优化请求体构建逻辑，排除内部模型额外键

src/providers/openai.rs

@@ -9,6 +9,11 @@ use crate::bus::message::ContentBlock;
 use super::{ChatCompletionRequest, ChatCompletionResponse, LLMProvider, ToolCall};
 use super::traits::Usage;
 
+const INTERNAL_MODEL_EXTRA_KEYS: &[&str] = &[
+    "tool_call_arguments_json",
+    "mock_response_content",
+];
+
 fn convert_content_blocks(blocks: &[ContentBlock]) -> Value {
     if blocks.len() == 1 {
         if let ContentBlock::Text { text } = &blocks[0] {
@@ -81,16 +86,34 @@ impl OpenAIProvider {
             .unwrap_or(false)
     }
 
-    fn serialize_tool_arguments(&self, arguments: &Value) -> Value {
-        if self.uses_json_tool_arguments() {
-            arguments.clone()
-        } else {
-            Value::String(
-                serde_json::to_string(arguments).unwrap_or_else(|_| "null".to_string()),
-            )
+    fn normalize_tool_arguments(&self, arguments: &Value) -> Value {
+        match arguments {
+            Value::String(raw) => serde_json::from_str(raw).unwrap_or_else(|_| arguments.clone()),
+            _ => arguments.clone(),
         }
     }
 
+    fn serialize_tool_arguments(&self, arguments: &Value) -> Value {
+        let normalized = self.normalize_tool_arguments(arguments);
+
+        if self.uses_json_tool_arguments() {
+            normalized
+        } else {
+            match normalized {
+                Value::String(raw) => Value::String(raw),
+                value => Value::String(
+                    serde_json::to_string(&value).unwrap_or_else(|_| "null".to_string()),
+                ),
+            }
+        }
+    }
+
+    fn request_model_extra(&self) -> impl Iterator<Item = (&String, &Value)> {
+        self.model_extra.iter().filter(|(key, _)| {
+            !INTERNAL_MODEL_EXTRA_KEYS.iter().any(|internal| internal == &key.as_str())
+        })
+    }
+
     fn build_request_body(&self, request: &ChatCompletionRequest) -> Value {
         let mut body = json!({
             "model": self.model_id,
@@ -142,7 +165,7 @@ impl OpenAIProvider {
             "max_tokens": request.max_tokens.or(self.max_tokens),
         });
 
-        for (key, value) in &self.model_extra {
+        for (key, value) in self.request_model_extra() {
             body[key] = value.clone();
         }
 
@@ -408,6 +431,78 @@ mod tests {
         let tool_calls = messages[0]["tool_calls"].as_array().unwrap();
 
         assert_eq!(tool_calls[0]["function"]["arguments"], json!({"expression": "1+1"}));
+        assert!(body.get("tool_call_arguments_json").is_none());
+    }
+
+    #[test]
+    fn test_build_request_body_preserves_raw_json_string_arguments() {
+        let provider = OpenAIProvider::new(
+            "test".to_string(),
+            "key".to_string(),
+            "https://example.com/v1".to_string(),
+            HashMap::new(),
+            120,
+            "gpt-test".to_string(),
+            None,
+            None,
+            HashMap::new(),
+        );
+
+        let request = ChatCompletionRequest {
+            messages: vec![Message {
+                role: "assistant".to_string(),
+                content: vec![ContentBlock::text("calling tool")],
+                reasoning_content: None,
+                tool_call_id: None,
+                name: None,
+                tool_calls: Some(vec![ToolCall {
+                    id: "call_1".to_string(),
+                    name: "calculator".to_string(),
+                    arguments: Value::String("{\"expression\":\"1+1\"}".to_string()),
+                }]),
+            }],
+            temperature: None,
+            max_tokens: None,
+            tools: None,
+        };
+
+        let body = provider.build_request_body(&request);
+        let messages = body["messages"].as_array().unwrap();
+        let tool_calls = messages[0]["tool_calls"].as_array().unwrap();
+
+        assert_eq!(tool_calls[0]["function"]["arguments"], "{\"expression\":\"1+1\"}");
+    }
+
+    #[test]
+    fn test_build_request_body_omits_internal_model_extra_keys() {
+        let provider = OpenAIProvider::new(
+            "test".to_string(),
+            "key".to_string(),
+            "https://example.com/v1".to_string(),
+            HashMap::new(),
+            120,
+            "gpt-test".to_string(),
+            None,
+            None,
+            HashMap::from([
+                ("tool_call_arguments_json".to_string(), Value::Bool(true)),
+                ("mock_response_content".to_string(), Value::String("stub".to_string())),
+                ("parallel_tool_calls".to_string(), Value::Bool(true)),
+            ]),
+        );
+
+        let request = ChatCompletionRequest {
+            messages: vec![Message::user("hello")],
+            temperature: None,
+            max_tokens: None,
+            tools: None,
+        };
+
+        let body = provider.build_request_body(&request);
+
+        assert!(body.get("tool_call_arguments_json").is_none());
+        assert!(body.get("mock_response_content").is_none());
+        assert_eq!(body["parallel_tool_calls"], Value::Bool(true));
     }
 
     #[test]