fix(usage): keep streamed call args in responses completion

The response.completed fallback rebuilt every call item with responsesCallInput(), which returns '{}' for a function_call lacking arguments. Since '{}' is truthy, ensureToolCall overwrote arguments already collected from streamed delta events. Guard the completed branch with responsesCallHasInput (matching the output_item.done branch) so empty/default inputs no longer clobber streamed args, and align its dedupe key with the streaming phase to avoid duplicate tool-call rendering when an item has no id. Drop the now-dead '工具调用' fallbacks since responsesCallName never returns empty.

frontend/src/features/usage/conversation/__tests__/stream.spec.ts

@@ -243,6 +243,45 @@ describe('Conversation stream compatibility', () => {
     })
   })
 
+  it('keeps streamed function_call arguments when response.completed omits them', () => {
+    const requestBody = {
+      model: 'gpt-5.5',
+      stream: true,
+      input: 'What is the weather?',
+    }
+    const rawSse = [
+      'event: response.created',
+      `data: ${JSON.stringify({ type: 'response.created', response: { id: 'resp_fc_1', object: 'response', model: 'gpt-5.5', status: 'in_progress' } })}`,
+      '',
+      'event: response.output_item.added',
+      `data: ${JSON.stringify({ type: 'response.output_item.added', output_index: 0, item: { id: 'fc_1', type: 'function_call', status: 'in_progress', call_id: 'call_1', name: 'get_weather', arguments: '' } })}`,
+      '',
+      'event: response.function_call_arguments.delta',
+      `data: ${JSON.stringify({ type: 'response.function_call_arguments.delta', output_index: 0, item_id: 'fc_1', delta: '{"city":' })}`,
+      '',
+      'event: response.function_call_arguments.delta',
+      `data: ${JSON.stringify({ type: 'response.function_call_arguments.delta', output_index: 0, item_id: 'fc_1', delta: '"SF"}' })}`,
+      '',
+      // 最终项故意不带 arguments：解析器不应用 '{}' 冲掉已收集的增量参数
+      'event: response.completed',
+      `data: ${JSON.stringify({ type: 'response.completed', response: { id: 'resp_fc_1', object: 'response', model: 'gpt-5.5', status: 'completed', output: [{ id: 'fc_1', type: 'function_call', status: 'completed', call_id: 'call_1', name: 'get_weather' }] } })}`,
+      '',
+      'data: [DONE]',
+      '',
+    ].join('\n')
+
+    const parsed = parseResponse(rawSse, requestBody, 'openai:responses')
+    // 命中同一 key，不重复渲染
+    expect(parsed.messages).toHaveLength(1)
+    expect(parsed.messages[0]?.content).toHaveLength(1)
+    expect(parsed.messages[0]?.content[0]).toMatchObject({
+      type: 'tool_use',
+      toolName: 'get_weather',
+      toolId: 'call_1',
+      input: '{"city":"SF"}',
+    })
+  })
+
   it('renders HTML-entity encoded OpenAI tool arguments as formatted JSON', () => {
     const requestBody = {
       model: 'gpt-5.4',

frontend/src/features/usage/conversation/openai.ts

@@ -698,8 +698,9 @@ export class OpenAIParser implements ApiFormatParser {
 
           // 从 output 中提取文本和工具调用（备用方案）
           if (Array.isArray(response?.output)) {
-            for (const rawItem of response.output as unknown[]) {
-              const item = rawItem as RawObject
+            const output = response.output as unknown[]
+            for (let index = 0; index < output.length; index++) {
+              const item = output[index] as RawObject
               if (textParts.length === 0 && item?.type === 'message' && Array.isArray(item?.content)) {
                 for (const rawContent of item.content as unknown[]) {
                   const content = rawContent as RawObject
@@ -710,12 +711,14 @@ export class OpenAIParser implements ApiFormatParser {
               } else if (this.isResponsesCallItemType(item.type)) {
                 const itemId = typeof item.id === 'string' ? item.id : ''
                 const toolId = this.responsesCallId(item)
-                ensureToolCall(
-                  itemId || toolId,
-                  toolId,
-                  this.responsesCallName(item),
-                  this.responsesCallInput(item)
-                )
+                // 与流式阶段使用同一套 key 命中同一条工具调用，避免重复渲染
+                const key = itemId || toolId || outputIndexToToolKey.get(index) || String(index)
+                // 仅在最终项确实带有输入时才覆盖，避免用 '{}' 等默认值
+                // 冲掉已通过增量事件收集到的参数
+                const input = this.responsesCallHasInput(item)
+                  ? this.responsesCallInput(item)
+                  : ''
+                ensureToolCall(key, toolId, this.responsesCallName(item), input)
               }
             }
           }
@@ -1007,7 +1010,7 @@ export class OpenAIParser implements ApiFormatParser {
 
     // Responses API call item -> 工具调用
     if (this.isResponsesCallItemType(itemType)) {
-      const toolName = this.responsesCallName(item) || '工具调用'
+      const toolName = this.responsesCallName(item)
       const args = this.formatJson(this.responsesCallInput(item))
       return createMessageBlock('assistant', [
         createToolUseRenderBlock(toolName, args, this.responsesCallId(item)),
@@ -1136,7 +1139,7 @@ export class OpenAIParser implements ApiFormatParser {
         } else if (this.isResponsesCallItemType(item.type)) {
           blocks.push(createMessageBlock('assistant', [
             createToolUseRenderBlock(
-              this.responsesCallName(item) || '工具调用',
+              this.responsesCallName(item),
               this.formatJson(this.responsesCallInput(item)),
               this.responsesCallId(item)
             ),