diff --git a/electron/harness/adapters/agnes-ai.adapter.ts b/electron/harness/adapters/agnes-ai.adapter.ts
index 7e5e52c..98fcc81 100644
--- a/electron/harness/adapters/agnes-ai.adapter.ts
+++ b/electron/harness/adapters/agnes-ai.adapter.ts
@@ -26,7 +26,7 @@ export class AgnesAdapter extends DeepSeekAdapter {
    *
    * 差异：
    * 1. Thinking 模式使用 chat_template_kwargs
-   * 2. 图片使用 OpenAI 多模态 content 数组格式
+   * 2. 图片处理由基类 DeepSeekAdapter.toNativeRequest 完成（OpenAI 多模态格式）
    */
   protected override toNativeRequest(request: MetonaRequest): Record<string, unknown> {
     const base = super.toNativeRequest(request) as Record<string, unknown>;
@@ -43,28 +43,6 @@ export class AgnesAdapter extends DeepSeekAdapter {
       base.max_tokens = 65536;
     }
 
-    // 图片处理：将 images 转为 OpenAI 多模态 content 数组格式
-    const messages = base.messages as Array<Record<string, unknown>>;
-    for (let i = 0; i < messages.length; i++) {
-      const msg = messages[i];
-      // 找到对应的原始消息（跳过 system 消息）
-      const origMsg = request.messages.filter((m) => m.role !== 'system')[i];
-      if (!origMsg?.images || origMsg.images.length === 0) continue;
-
-      // 将 content 转为数组格式：[{type: "text", text: ...}, {type: "image_url", ...}]
-      const contentParts: Array<Record<string, unknown>> = [];
-      if (msg.content && typeof msg.content === 'string') {
-        contentParts.push({ type: 'text', text: msg.content });
-      }
-      for (const img of origMsg.images) {
-        contentParts.push({
-          type: 'image_url',
-          image_url: { url: img.url, detail: img.detail ?? 'auto' },
-        });
-      }
-      msg.content = contentParts;
-    }
-
     return base;
   }
 }
diff --git a/electron/harness/adapters/deepseek.adapter.ts b/electron/harness/adapters/deepseek.adapter.ts
index 6b5c5cf..fe010b8 100644
--- a/electron/harness/adapters/deepseek.adapter.ts
+++ b/electron/harness/adapters/deepseek.adapter.ts
@@ -263,7 +263,26 @@ export class DeepSeekAdapter extends BaseAdapter {
         ].filter(Boolean).join('\n\n'),
       },
       ...request.messages.filter((m) => m.role !== 'system').map((m) => {
-        const msg: Record<string, unknown> = { role: m.role, content: m.content };
+        const msg: Record<string, unknown> = { role: m.role };
+
+        // 多模态图片处理：将 images 转为 OpenAI content 数组格式
+        // [{"type":"text","text":"..."}, {"type":"image_url","image_url":{"url":"data:..."}}]
+        if (m.images && m.images.length > 0) {
+          const contentParts: Array<Record<string, unknown>> = [];
+          if (m.content) {
+            contentParts.push({ type: 'text', text: m.content });
+          }
+          for (const img of m.images) {
+            contentParts.push({
+              type: 'image_url',
+              image_url: { url: img.url, detail: img.detail ?? 'auto' },
+            });
+          }
+          msg.content = contentParts;
+        } else {
+          msg.content = m.content;
+        }
+
         if (m.role === 'assistant' && m.toolCalls?.length) {
           msg.tool_calls = m.toolCalls.map((tc) => ({
             id: tc.id,
diff --git a/src/stores/agent-store.ts b/src/stores/agent-store.ts
index 173b235..17c81b1 100644
--- a/src/stores/agent-store.ts
+++ b/src/stores/agent-store.ts
@@ -220,33 +220,34 @@ export const useAgentStore = create<AgentState>((set, get) => ({
     }
 
     if (sessionId && window.metona?.agent?.sendMessage) {
-      // 构建发给 LLM 的 content：纯用户文本 + 文件 JSON（无文字描述）
+      // 构建发给 LLM 的消息
+      // images 参数由 ChatInput 传入（已从附件中提取 base64 data URL）
       let llmContent = content;
-      const images: Array<{ url: string; detail?: 'low' | 'high' | 'auto' }> = [];
+      const llmImages: Array<{ url: string; detail?: 'low' | 'high' | 'auto' }> = [
+        ...(images ?? []),
+      ];
 
       if (attachments && attachments.length > 0) {
         const parts: string[] = [];
         for (const att of attachments) {
-          if (att.type === 'image' && att.preview) {
-            // 图片：直接加入 images 数组
-            images.push({ url: att.preview, detail: 'auto' });
-          } else {
-            // 所有文件：JSON 格式，Base64 编码内容
-            const ext = att.name.split('.').pop() ?? 'unknown';
-            let base64Content = '';
-            if (att.textContent) {
-              base64Content = btoa(unescape(encodeURIComponent(att.textContent)));
-            } else if (att.preview) {
-              // 二进制文件从 data URL 提取 base64
-              base64Content = att.preview.split(',')[1] ?? '';
-            }
-            parts.push(JSON.stringify({
-              file_name: att.name,
-              file_type: ext,
-              context_encode: 'Base64',
-              context: base64Content,
-            }));
+          if (att.type === 'image') {
+            // 图片已在 images 参数中处理，跳过
+            continue;
           }
+          // 非图片文件：JSON 格式，Base64 编码内容
+          const ext = att.name.split('.').pop() ?? 'unknown';
+          let base64Content = '';
+          if (att.textContent) {
+            base64Content = btoa(unescape(encodeURIComponent(att.textContent)));
+          } else if (att.preview) {
+            base64Content = att.preview.split(',')[1] ?? '';
+          }
+          parts.push(JSON.stringify({
+            file_name: att.name,
+            file_type: ext,
+            context_encode: 'Base64',
+            context: base64Content,
+          }));
         }
         llmContent = parts.join('\n') + (content ? '\n\n' + content : '');
       }
@@ -254,7 +255,7 @@ export const useAgentStore = create<AgentState>((set, get) => ({
       const messageWithImages = {
         ...userMessage,
         content: llmContent,
-        images: images.length > 0 ? images : undefined,
+        images: llmImages.length > 0 ? llmImages : undefined,
       };
       window.metona.agent.sendMessage(messageWithImages, sessionId).catch(() => {});
     }