feat: Add merge_system_prompt option with bug fixes

core/migrations/0036_openaiagent_merge_system_prompt.py

@@ -0,0 +1,18 @@
+# Generated by Django 5.2.5 on 2025-12-11 09:22
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('core', '0035_alter_openaiagent_max_tokens_digest'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='openaiagent',
+            name='merge_system_prompt',
+            field=models.BooleanField(default=False, help_text="Enable for models that don't support system system instructions (e.g., Gemma 3)", verbose_name='Merge System Prompt to User Message'),
+        ),
+    ]

core/models/agent.py

@@ -93,6 +93,11 @@ class OpenAIAgent(Agent):
         default=0,
         help_text=_("Maximum requests per minute (0 = no limit)"),
     )
+    merge_system_prompt = models.BooleanField(
+        _("Merge System Prompt to User Message"),
+        default=False,
+        help_text=_("Enable for models that don't support system system instructions (e.g., Gemma 3)")
+    )
     EXTRA_HEADERS = {
         "HTTP-Referer": "https://www.rssbox.app",
         "X-Title": "RSSBox",
@@ -260,9 +265,30 @@ def completions(
 
             # 应用速率限制
             self._wait_for_rate_limit()
-
-            # 计算系统提示的token占用
-            system_prompt_tokens = get_token_count(system_prompt)
+
+            if self.merge_system_prompt:
+                merged_content = f"{system_prompt}\n\n{text}"
+                messages = [
+                    {"role": "user", "content": merged_content}
+                ]
+                # 当合并 system prompt 时，system_prompt_tokens 为 0（因为已包含在 merged_content 中）
+                system_prompt_tokens = 0
+                input_tokens = get_token_count(merged_content)
+            else:
+                messages = [
+                    {
+                        "role": "system",
+                        "content": system_prompt,
+                    },
+                    {
+                        "role": "user", 
+                        "content": text
+                    }
+                ]
+                # 计算系统提示的token占用
+                system_prompt_tokens = get_token_count(system_prompt)
+                input_tokens = get_token_count(system_prompt) + get_token_count(text)
+
             # 获取最大可用token数（保留buffer）
             if self.max_tokens == 0:
                 task_manager.submit_task(
@@ -274,9 +300,19 @@ def completions(
                     "max_tokens is not set, Please wait for the model limit detection to complete"
                 )
 
-            max_usable_tokens = (
-                self.max_tokens - system_prompt_tokens - 100
-            )  # 100 token buffer
+            # 计算最大可用token数
+            # 当 merge_system_prompt=True 时，system_prompt 已包含在 merged_content 中，所以只需要考虑 text 的 token
+            if self.merge_system_prompt:
+                # 合并模式下，需要从总限制中减去 system_prompt 的 token（因为它会占用输入空间）
+                system_prompt_token_cost = get_token_count(system_prompt)
+                max_usable_tokens = (
+                    self.max_tokens - system_prompt_token_cost - 100
+                )  # 100 token buffer
+            else:
+                max_usable_tokens = (
+                    self.max_tokens - system_prompt_tokens - 100
+                )  # 100 token buffer
+
             # 检查文本长度是否需要分块
             if get_token_count(text) > max_usable_tokens:
                 logger.info(
@@ -308,7 +344,7 @@ def completions(
                 return {"text": result_text, "tokens": tokens}
 
             # 计算合理的输出token限制
-            input_tokens = get_token_count(system_prompt) + get_token_count(text)
+            # input_tokens 已经在上面根据 merge_system_prompt 的情况正确计算了，直接使用
             # 输出token限制 = 模型总限制 - 输入token - 安全缓冲
             output_token_limit = int(max(4096, (self.max_tokens - input_tokens) * 0.8))
 
@@ -328,10 +364,7 @@ def completions(
             res = client.with_options(max_retries=3).chat.completions.create(
                 extra_headers=self.EXTRA_HEADERS,
                 model=self.model,
-                messages=[
-                    {"role": "system", "content": system_prompt},
-                    {"role": "user", "content": text},
-                ],
+                messages=messages,
                 **call_kwargs,
             )
             if (